Historical and projected climate (1901–2050) and hydrologic response of karst aquifers, and species vulnerability in south-central Texas and western South Dakota


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Historical and projected climate (1901–2050) and hydrologic response of karst aquifers, and species vulnerability in south-central Texas and western South Dakota

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Historical and projected climate (1901–2050) and hydrologic response of karst aquifers, and species vulnerability in south-central Texas and western South Dakota
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Scientific Investigations Report
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Stamm, John F.
Poteet, Mary F.
Symstad, Amy J.
Musgrove, MaryLynn
Long, Andrew J. et al
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Two karst aquifers, the Edwards aquifer in the Balcones Escarpment region of south-central Texas and the Madison aquifer in the Black Hills of western South Dakota, were evaluated for hydrologic response to projected climate change through 2050. Edwards aquifer sites include Barton Springs, the Bexar County Index Well, and Comal Springs. Madison aquifer sites include Spearfish Creek and Rhoads Fork Spring. Climate projections at sites were based on output from the Community Climate System Model of global climate, linked to the Weather Research and Forecasting (WRF) model of regional climate. The WRF model output was bias adjusted to match means for 1981–2010 from records at weather stations near Madison and Edwards aquifer sites, including Boerne, Texas, and Custer and Lead, South Dakota. Hydrologic response at spring and well sites was based on the Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model. The WRF model climate projections for 2011–50 indicate a significant upward trend in annual air temperature for all three weather stations and a significant downward trend in annual precipitation for the Boerne weather station. Annual springflow simulated by the RRAWFLOW model had a significant downward trend for Edwards aquifer sites and no trend for Madison aquifer sites. Flora and fauna that rely on springflow from Edwards and Madison aquifer sites were assessed for vulnerability to projected climate change on the basis of the Climate Change Vulnerability Index (CCVI). The CCVI is determined by the exposure of a species to climate, the sensitivity of the species, and the ability of the species to cope with climate change. Sixteen species associated with springs and groundwater were assessed in the Balcones Escarpment region. The Barton Springs salamander (Eurycea sosorum) was scored as highly vulnerable with moderate confidence. Nine species—three salamanders, a fountain darter (Etheostoma fonticola), three insects, and two amphipods—were scored as moderately vulnerable. The remaining six species—four v
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Scientific Investigations Report, Vol. 2014-5089 (2014).

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U.S. Department of the Interior U.S. Geological Survey Scientific Investigations Report 2014 Prepared in cooperation with the Department of Interior South-Central Climate Science Center Historical and Projected Climate (1901–2050) and Hydrologic Response of Karst Aquifers, and Species Vulnerability in South-Central Texas and Western South Dakota

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Cover photographs . Upper left, Downstream view of Spearfish Creek at Spearfish, South Dakota. Photograph by Louis Leader Charge, U.S. Geological Survey. Upper right, Barton Springs pool, Austin, Texas. The spring discharges from beneath the limestone ledges, visible at the upper end of the pool. Photograph by David Johns, City of Austin, Texas. Bottom right, Barton Springs salamander. Photograph by Lisa O’Donnell, City of Austin, Texas. Bottom left, American dipper. Photograph by Dave Menke, U.S. Fish and Wildlife Service.

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Historical and Projected Climate (1901– 2050) and Hydrologic Response of Karst Aquifers, and Species Vulnerability in South-Central Texas and Western South Dakota By John F. Stamm, Mary F. Poteet, Amy J. Symstad, MaryLynn Musgrove, Andrew J. Long, Barbara J. Mahler, and Parker A. Norton Prepared in cooperation with the Department of Interior South-Central Climate Science Center Scientific Investigations Report 2014 U.S. Department of the Interior U.S. Geological Survey

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U.S. Department of the Interior SALLY JEWELL, Secretary U.S. Geological Survey Suzette M. Kimball, Acting Director U.S. Geological Survey, Reston, Virginia: 2015 For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1–ASK–USGS. For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprod To order this and other USGS information products, visit http://store.usgs.gov Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner. Suggested citation: Stamm, J.F., Poteet, M.F., Symstad, A.J., Musgrove, MaryLynn, Long, A.J., Mahler, B.J., and Norton, P.A., 2015, Historical and projected climate (1901) and hydrologic response of karst aquifers, and species vulnerability in south-central Texas and western South Dakota: U.S. Geological Survey Scientific Investigations Report 2014, 59 p., plus supplements, http://dx.doi.org/10.3133/sir20145089 . ISSN 2328-0328 (online)

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iii Contents Acknowledgments ...................................................................................................................................... viii Abstract ........................................................................................................................................................... 1 Introduction ..................................................................................................................................................... 1 Purpose and Scope .............................................................................................................................. 2 Geologic and Hydrologic Settings ..................................................................................................... 2 Climatic Setting ..................................................................................................................................... 4 Historical Climate ......................................................................................................................... 4 Paleoclimate ................................................................................................................................. 5 Ecological Setting ................................................................................................................................. 8 Methods and Models .................................................................................................................................. 10 Weather Station Data ......................................................................................................................... 12 Climate Models .................................................................................................................................... 13 Community Climate System Model ......................................................................................... 14 Weather Research and Forecasting Model .......................................................................... 15 Hydrologic Model ................................................................................................................................ 21 Species Assessment .......................................................................................................................... 21 Historical and Projected Climate and Hydrologic Response ............................................................... 24 Climate Trends and Statistics ........................................................................................................... 25 Climate and Hydrologic Response ................................................................................................... 27 Baseline and Projected Climate and Hydrologic Response ........................................................ 29 Trends .......................................................................................................................................... 29 Frequencies and Extremes of Events ..................................................................................... 35 Aridity Index ................................................................................................................................ 35 Species Vulnerability to Projected Climate and Hydrologic Response .............................................. 38 Species Vulnerability .......................................................................................................................... 39 Differences Between Regions .......................................................................................................... 46 Evaluation of the Approach ............................................................................................................... 46 Summary ........................................................................................................................................................ 47 References Cited .......................................................................................................................................... 48 Supplement 1. Data Tables for Species Vulnerability Assessment ..................................................... 60 Supplement 2. Paleoclimate Inventory .................................................................................................... 60 Supplement 3. Weather Research and Forecasting Model Namelist Files and Bias Adjustments ..................................................................................................................................... 60

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iv Figures 1. Map showing study area and locations of weather stations, streamgages, and wells used in the analyses and models .................................................................................... 3 2. Isohyetal and isothermal maps for the regions of the Balcones Escarpment and Black Hills, based on annual values computed from output from the Parameter-elevation Regressions on Independent Slopes Model averaged for 1901 ....................................................................................................................................... 6 3. Graph showing concentrations of greenhouse gases on the basis of the Vostok ice core, and current and projected concentrations ............................................................. 7 4. Map showing ecoregions and land cover of Edwards aquifer sites and the surrounding region ....................................................................................................................... 9 5. Map showing ecoregions and land cover of Madison aquifer sites and the surrounding region ..................................................................................................................... 11 6. Diagram showing linkage of model components .................................................................. 12 7. Graphs showing time series of annual mean surface air temperature and total precipitation during 1901 for the area of the Great Plains for three general circulation models, and during 1901 for the Parameter-elevation Regressions on Independent Slopes Model .......................................................................... 16 8. Graphs showing mean monthly surface air temperature and total precipitation during 1901 for the area of the Great Plains for three general circulation models and for the Parameter-elevation Regressions on Independent Slopes Model ............................................................................................................................................ 17 9. Map showing the Weather Research and Forecasting model domain extent showing land-surface altitudes at the 36-kilometer resolution .......................................... 18 10. Graphs showing time series of annual mean surface air temperature and total precipitation for the area of the Great Plains from the Community Climate System Model, version 3, two simulations from the Weather Research and Forecasting model, and the Parameter-elevation Regressions on Independent Slopes Model ............................................................................................................................... 19 11. Graphs showing annual total precipitation, annual mean daily air temperatures, and 10-year moving means of annual values of weather station records and adjusted output from the Weather Research and Forecasting Model for selected weather stations ......................................................................................................................... 26 12. Graphs showing mean monthly precipitation and air temperature of weather station records and adjusted output from the Weather Research and Forecasting model for selected weather stations ....................................................................................... 28 13. Graphs showing annual mean air temperature, annual total precipitation, and annual mean springflow or water-table level for Edwards and Madison aquifer sites based on observed weather station records, output from the Weather Research and Forecasting model, and output from the Rainfall-Response Aquifer and Watershed Flow model ...................................................................................................... 30 14. Graph showing number of days and consecutive days in a year that the maximum daily air temperature exceeded 36 degrees Celsius at the Lead, South Dakota, weather station ............................................................................................................ 40 15. Graph showing aridity index for start of records through 2050 for selected weather stations ......................................................................................................................... 41

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v Tables 1. Weather stations used to synthesize climate records for the five Rainfall-Response Aquifer and Watershed Flow model sites and weather station period of records ........................................................................................................... 13 2. Description and location for weather stations used to quantify climate variability ....... 13 3. Dynamical mesoscale models for North American climate and associated Atmosphere-Ocean General Circulation Model .................................................................... 14 4. General description of physics schemes used in the Weather Research and Forecasting model ...................................................................................................................... 20 5. Factors scored in the Climate Change Vulnerability Index and climate and hydrologic input used for scoring ............................................................................................ 23 6. Mean annual precipitation and air temperature for years 1943, 1943, and 2011 for selected weather stations ............................................................................ 25 7. Results of Kendall-tau nonparametric test of significance of trends for records and climate projections for selected weather stations ....................................................... 27 8. Anomalies of climate variables for selected weather stations .......................................... 29 9. Statistical significance and direction of trends in monthly and annual precipitation and air temperatures at selected weather stations for the period spanning the start of weather station records through 1975 .............................................. 32 10. Statistical significance and direction of trends in projected monthly and annual precipitation and air temperatures at selected weather stations for 2011 ................ 33 11. Statistical significance and direction of trends in monthly and annual precipitation and air temperatures at selected weather stations for the period spanning the start of the weather station record through 2050 ......................................... 34 12. Climate anomalies, computed as mean monthly or mean annual for 20410 minus mean monthly or mean annual for start of record through 1975 at selected weather stations ......................................................................................................................... 36 13. Statistical significance and direction of trends in monthly mean and annual mean springflow or water-table level at Edwards and Madison aquifer sites based on output from the Rainfall-Response Aquifer and Watershed Flow model .......................... 37 14. Exceedance values of daily climate variables for selected weather stations, on the basis of observational records for the start of record through 1975 and output from the Weather Research and Forecasting model for 2041 ...................................... 38 15. Exceedance values of simulated daily springflow or water-table level for Edwards and Madison aquifer sites based on output from Rainfall-Response Aquifer and Watershed Flow model for the start of record through 1975 and for 2041–50 ................. 39 16. Range in annual temperature measured as July mean daily maximum air temperature minus January mean daily minimum air temperature for start of weather station record (SOR) through 1975 for selected weather stations ..................... 40 17. Percentage of years in listed time periods of aridity index classifications for weather stations for three periods: start of weather station record to 1975, 2041, and SOR ............................................................................................................. 41 18. Climate change vulnerability, confidence in that assessment, and vulnerability to other anthropogenic threats for selected karst-hydrology-dependent species in the Balcones Escarpment and Black Hills regions ............................................................... 42 19. Climate and hydrologic input for factors in the Climate Change Vulnerability Index for each weather station/hydrologic site ............................................................................... 44

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vi Supplement Tables S1. Species of conservation concern that depend strongly on karst hydrology in the Balcones Escarpment and Black Hills regions, their conservation status and restriction to the assessment area, and whether their vulnerability to climate change was scored for this report .......................................................................................... 60 S1. Climate Change Vulnerability Index factor scores, information supporting those scores, and the CCVI results for select karst-hydrology-dependent species in the Balcones Escarpment and Black Hills regions ...................................................................... 60 S2. Review and inventory of local and regional paleoclimatic studies with relevance for the study areas ...................................................................................................................... 60 S3. Bias corrections applied to the Weather Research and Forecasting Model output interpolated to the locations of weather stations for modeled sites ................................. 61

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vii Conversion Factors SI to Inch/Pound Multiply By To obtain Length millimeter (mm) 0.03937 inch (in.) meter (m) 3.281 foot (ft) kilometer (km) 0.6214 mile (mi) kilometer (km) 0.5400 mile, nautical (nmi) meter (m) 1.094 yard (yd) Flow rate cubic meter per second (m 3 /s) 15,850 gallon per minute (gal/min) Temperature in degrees Celsius (C) may be converted to degrees Fahrenheit (F) as follows: F=(1.8C)+32 Vertical coordinate information is referenced to the North American Vertical Datum of 1988 (NAVD 88). Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83). Altitude, as used in this report, refers to distance above the vertical datum. Water year is the 12-month period, October 1 through September 30, and is designated by the calendar year in which it ends. Concentrations of chemical constituents in water are given in milligrams per liter (mg/L).

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viii Abbreviations ~ approximately less than or equal to 20C3M 20th Century Climate in Coupled Models AOGCM Atmosphere-Ocean General Circulation Model CCSM3 Community Climate System Model, version 3.0 CCVI Climate Change Vulnerability Index CGCM3 Canadian Centre for Climate Modeling and Analysis General Circulation Model, version 3.1/T63 CO 2 carbon dioxide E N-S Nash-Sutcliffe coefficient of efficiency GFDL CM2 Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 IRF impulse-response function Ma million years ago NOAA National Oceanic and Atmospheric Administration P precipitation p -value probability value PAGES 2k Past Global Changes research on the last 2,000 years ppb parts per billion ppmv parts per million by volume PRISM Parameter-elevation Regressions on Independent Slopes Model RegCM Regional Climate Model RRAWFLOW Rainfall-Response Aquifer and Watershed Flow SOR start of record SRES Special Report on Emission Scenarios T max maximum air temperature T mean mean air temperature T min minimum air temperature WPS Weather Research and Forecasting (WRF) model Preprocessing System WRF Weather Research and Forecasting YBP years before present Acknowledgments This study was supported by the Department of Interior South-Central Climate Science Center.

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Historical and Projected Climate (1901–2050) and Hydrologic Response of Karst Aquifers, and Species Vulnerability in South-Central Texas and Western South Dakota By John F. Stamm, 1 Mary F. Poteet, 2 Amy J. Symstad, 1 MaryLynn Musgrove, 1 Andrew J. Long, 1 Barbara J. Mahler, 1 and Parker A. Norton 1 1 U.S. Geological Survey. 2 University of Texas, Austin. Abstract Two karst aquifers, the Edwards aquifer in the Balcones Escarpment region of south-central Texas and the Madison aquifer in the Black Hills of western South Dakota, were evaluated for hydrologic response to projected climate change through 2050. Edwards aquifer sites include Barton Springs, the Bexar County Index Well, and Comal Springs. Madison aquifer projections at sites were based on output from the Community Climate System Model of global climate, linked to the Weather 1981 from records at weather stations near Madison and Edwards aquifer sites, including Boerne, Texas, and Custer and Lead, South Dakota. Hydrologic response at spring and trend in annual air temperature for all three weather stations Edwards aquifer sites and no trend for Madison aquifer sites. and Madison aquifer sites were assessed for vulnerability to projected climate change on the basis of the Climate Change Vulnerability Index (CCVI). The CCVI is determined by the exposure of a species to climate, the sensitivity of the species, and the ability of the species to cope with climate change. Sixteen species associated with springs and groundwater were assessed in the Balcones Escarpment region. The Barton Springs salamander ( Eurycea sosorum ) was scored as highly salamanders, a fountain darter ( Etheostoma fonticola ), three the Barton cavesnail ( Stygopyrgus bartonensis ), and a cave vulnerable and evidence does not support change in abundance or range of the species). Vulnerability of eight species associ dipper ( Cinclus mexicanus ) and the lesser yellow lady’s slipper ( ) were scored as moderately vulern Equisetum scirpoides ) and autumn willow ( Salix serissima ) were also able/presumed stable or not vulnerable/increase likely (not vulnerable and evidence supporting an increase in abundance or range of the species). Lower vulnerability scores for the Black Hills species in comparison to the Balcones Escarpment species the historical period, and high thermal tolerance of many of the species for the Black Hills. Importantly, climate change vulner ability scores differed substantially for Edwards aquifer species in increased vulnerability scores for 12 of the 16 species. Introduction Karst aquifers are important groundwater resources in joints, faults, bedding planes, and solution cavities (Palmer, 1990), and can exhibit large short-term variability in hydro karst aquifers are likely to respond rapidly to climate change

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2 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota in areas where urban development imparts additional stresses and ecosystems associated with karst aquifers and terranes also are extremely sensitive to changes in hydrologic conditions species live in subterranean habitats, many of which are associ ated with karst aquifers and terranes (Culver and others, 2000). projected climate change through 2050, based on the A2 emis at sites within two regions of karst terrane: the Balcones Escarpment of south-central Texas and the Black Hills of aquifer (hereinafter the Edwards aquifer) and the Madison aquifer, respectively. Examined sites in these two regions are referred to as Edwards and Madison aquifer sites. Municipali ties in both regions, and State parks and national forests and parks in the Black Hills, rely on water resources from these The associated ecosystems support federally listed endangered are listed in supplemental table S1). Vulnerability of species to projected climate change was assessed using the Climate Change Vulnerability Index (CCVI) (Young and others, 2012). The CCVI uses historical table level to determine the vulnerability of selected species to climate and associated hydrogeologic change (factors used to estimate vulnerability of selected species are listed in supple mental table S1). Projected climate through 2050 was simu lated using the Community Climate System Model, version 3.0 (CCSM3) (Collins and others, 2004), of global climate to project the effects of global climate change on local karst aquifers and springs, and reliant species. Purpose and Scope The purpose of this report is to describe the effects of historical and projected climate (1901) and hydrologic response of karst aquifers and species vulnerability in southcentral Texas and western South Dakota. The methodology used to assess species vulnerability at Edwards and Madison aquifer sites based on models that operate at scales ranging methodology and application on the basis of multiple climate models and multiple emission scenarios is beyond the scope of this report. The selection of climate models and the green vulnerability of species to climate change and hydrologic described could be applied to karst regions elsewhere, or for species not included in this study. Geologic and Hydrologic Settings The geologic and hydrologic settings of the Balcones Escarpment of Texas and the Black Hills of South Dakota are characterized by plateaus of resistant carbonate rocks. The Balcones Escarpment is named for resistant rocks expressed by steps or “balconies” in the landscape, which rises from the Coastal Plain to the east of the Balcones Escarpment, to the geology and hydrology of south-central Texas and the area of Abbott (1975), Abbott and Woodruff (1986), Barker and Ardis (1996), Sharp and Banner (1997), and Lindgren and others The Balcones Escarpment is the surface manifesta tion of the Balcones fault zone, which consists of a series of high-angle normal en echelon down-toward-the-coast faults that were active during the Miocene Epoch [24 million years ago (Ma)]. The Edwards aquifer, a karst aquifer that lies along the Balcones Escarpment, is part of the larger Edwards-Trinity aquifer system and is one of the most perme at 1.58 cubic meters per second (m 3 /s) (25,000 gallons per minute) (Swanson, 1991). Watersheds to the west contrib ute most of the recharge to the aquifer (Burchett and others, Mexico drain the Edwards Plateau and recharge the aquifer as they cross the Balcones fault zone. The Edwards aquifer natural discharge occurring at large springs, such as Barton The regional geologic setting of western South Dakota and the Black Hills has been summarized by Gries (1996) and Carter and others (2002), and described and mapped in detail Dewitt, 2008). Precambrian-age igneous and metamorphic

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Introduction 3 Rocky Mountain system figure 1 Spearfish Creek Lead Custer SpearfishRapid City Hot Springs 103' 104' 44' 44' 43' Black Hills region EXPLANATIONStreamgage and identifier Spring or spring complex and identifier Well and identifier Weather station and identifier Centroid for interpolation of weather recordsEdwards aquifer surface-recharge areaEdwards aquifer below land surface (confined) Madison aquifer surface-recharge area Madison aquifer below land surface (confined)Hydrogeologic unitNebraska Sand Hills ecoregionPhysical division and ecoregion Black Hills A Austin San AntonioComal Springs Comal Springs Barton Springs Bexar County Index Well Bexar County Index Well Hondo Hondo Boerne Rockspring 18 SW Dripping Springs 6 E 98 99 100 31 30 29 Balcones Escarpment regionBalcones EscarpmentTransverse Mercator, North American Datum 1983, Elevation dataset: National Elevation Dataset (Gesch and others, 2002; Gesch, 2007)Red Valley Limestone Plateau Harney PeakRed Valley Crystalline core Edwards Plateau Coastal Plain Moon Lake Gulf of Mexico Rapid CreekSpearfish Creek 0 50 KILOMETERS 25 0 10 20 MILES 0 50 KILOMETERS 25 0 10 20 MILES Great Plains province Minnelusa aquifer surface-recharge area Spearfish Creek Aquifer extents from Love and Christiansen (1985), Ashworth and Hopkins (1995), and Strobel and others (1999) Physical divisions from Fenneman (1931) Rhoads Fork SpringWYOMING SOUTH DAKOTA Figure 1. S tudy area and locations of weather stations, streamgages, and wells used in the analyses and models . Physical divisions and ecoregions relevant to the study area are labeled.

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4 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota rocks are exposed in the Central Basin of the Black Hills 65 Ma and ended about 55 Ma (Lisenbee and DeWitt, 1993). The Central Basin, also known as the crystalline core, is encircled by a layered series of Paleozoic and Mesozoic sedimentary rocks, which include the resistant Mississippianage Madison Limestone (locally referred to as the Pahasapa Limestone) and the overlying Pennsylvanianand Permianuplifted Black Hills. The Limestone Plateau is located on the western side of the Black Hills along the South Dakota and Wyoming border, where large outcrops of the Madison Lime of generally low relief (Carter and others, 2002). The Black which is underlain by red clastic rocks of the Triassic-age other units. The foothills of the Black Hills are underlain by creates a prominent hogback that stands hundreds of meters above the surrounding plains and generally marks the bound ary between the Black Hills and the plains (Gries, 1996). Less resistant Cretaceous-age marine deposits, such as the Pierre Shale, underlie the surrounding plains. Cenozoic sedimentary rocks unconformably overlie Cretaceous-age marine deposits and record the history of uplift and erosion of the Black Hills during and after the Laramide orogeny. Tertiary-age igneous units intruded primarily between 58 and 50 Ma in the northern Black Hills (Lisenbee and DeWitt, 1993). The regional hydrologic setting of the Black Hills includes the Madison aquifer, which is composed of Devo nian-age Englewood Limestone and the Madison Limestone (Strobel and others, 1999). The characteristics of the Madison aquifer are described in detail by Carter and others (2002). The aquifer generally is within the upper karstic part of the Madison Limestone and saturated thickness is less than 60 m where the Madison Limestone is exposed at land surface. The aquifer is susceptible to drought conditions, particularly in areas where the Madison Limestone is exposed at land surface (Carter and others, 2002). Streams draining the crystalline core of the Black Hills generally provide more recharge to the streams cross outcrops of the Madison Limestone before springs occur along the eastern edge of the Limestone Plateau in incised channels near the base of the Madison Limestone, of the last glacial advance (approximately 21,000 years ago), northeast (Downey and Dinwiddie, 1988). Climatic Setting The climatic setting of the study area is described in this section in terms of the historical climatic settings of the Balcones Escarpment and the Black Hills regions, and in terms of the global and regional paleoclimatic setting. Histori cal climate (1901 to 2000) provides a baseline and context for current (2013) climate. Global paleoclimatic events provide a reference for the magnitude of current and projected concen trations of greenhouse gases in the next century. Historical Climate The climate of south-central Texas is subtropical, with a regional gradient from subhumid in the east to semi-arid in the west (Bomar, 1995). The dominant moisture source is the Gulf of Mexico, which is supplemented by winter precipita tion from the west (Slade and Patton, 2003). The climate of 1985). Droughts lasting from many months to years have been documented in the region since the earliest settlers began keeping records (Texas State Historical Association, 2013). The 1950s multiyear drought commonly is used as the worstcase scenario for water-resources planning, although the 2011 Gammon, 2011). Some of the most extreme 1-day duration storms in the world have occurred along the Balcones Escarp ment, which can trigger high-intensity rain events (Slade, 1986). The Black Hills region has a continental climate charac terized by low precipitation, hot summers, cold winters, and with colder temperatures and higher precipitation at higher altitudes. The northern Black Hills is affected by moist air from the northwest, and the southern Black Hills is affected by drier air from the south-southeast. This produces a contrast in climate with mean precipitation ranging from 587 millimeters (mm) in the northern Black Hills to 415 mm in the southern The greatest amount of precipitation typically occurs during of below normal precipitation occurred during 1931 (“Dust occurred during 1941, 1962, and 1991 (Driscoll and others, 2000), relative to the 1961 climate normal. Spatial trends of historical climate of the Balcones Escarpment and Black Hills regions can be estimated on the total precipitation, and monthly mean of daily maximum air temperature and daily minimum air temperature to a

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Introduction 5 2.5-arc-minute grid for the conterminous United States. Grids grid points in the Balcones Escarpment region indicates a regional pattern of mean annual precipitation greater than 850 mm in the east decreasing to less than 500 mm in the pattern is a pattern of highest precipitation along the Balcones Escarpment. Mean annual values of daily minimum and daily maximum air temperature have a spatial pattern of greatest air-temperature gradients along the Balcones Escarpment, the Balcones Escarpment have a mean annual precipitation value of 746 mm, a mean annual maximum air temperature of 26.7 degrees Celsius (C), and a mean annual minimum air temperature of 13.1 C. points in the Black Hills region has a spatial pattern of increas ing mean annual precipitation and decreasing mean annual air temperature with higher altitude than the surrounding plains precipitation in lower elevations surrounding the Black Hills is approximately 350 to 400 mm, increasing with altitude to more than 750 mm in the northern Black Hills. Mean annual values of daily minimum and daily maximum air temperatures decrease with increasing altitude, with lowest mean annual temperatures in high altitude areas generally along the western surface-recharge area for the Madison aquifer have a mean annual precipitation value of 591 mm, and mean annual values of daily maximum and daily minimum air temperatures of 12.0 C and -3.2 C, respectively. The surface-recharge area of Edwards aquifer along the Balcones Escarpment on average receives about 150 mm more annual precipitation than does the surface-recharge area of the Madison Limestone in the Black Hills and is about 15 C warmer. Paleoclimate Paleoclimatology is the study of climate before historical records (Bradley, 1999). Paleoclimatic conditions can be esti mated from a variety of proxy sources including tree rings, ice cores, marine and lake sediments, and cave deposits (speleo thems). In this report, paleoclimate variability is described to place the projected climate estimated for the upcoming decades into the context of natural variability. Selected studies relevant to the Edwards and Madison aquifer sites also are summarized. Proxy sources and paleoclimate relevant to the sites included in this study and of general interest for the central and western United States have been compiled in supplemental table S2. It is generally accepted that global climate has cooled steadily since the beginning of the Tertiary Period (66 Ma) in response to a gradual trend of decreasing concentration The Tertiary Period was marked by periods of warmth, some of which were punctuated events associated with elevated 2 ) that might provide analogs to modern and projected climate trends (Kennett 2 has not been as high as it is today [mean concentration surpassed 400 parts per million by volume istration, 2013)] since at least the mid-Pliocene Epoch, 3.3 to 3.0 Ma (Solomon and others, 2007). Some studies estimate 2 during the midPliocene Epoch were 360 ppmv and temperature was 2 concentrations of less than 350 ppmv for 3.4 to 2.4 Ma, 2 concentrations did not reach modern concentrations near 400 ppmv until about 2 and methane during the late Quaternary can be determined from ice core records with relative accuracy (Petit and others, 1999), with greenhouse gas concentrations in ice core samples estimated at a temporal resolution of approximately 800 to 1,000 years. Present mean concentrations of greenhouse gases, including 2 [approximately (~) 393 ppmv] and methane (~1,800 ppb) (Blasing, 2013), exceed measurements from ice cores that glacial cycles, which each lasted about 100,000 years (Hays ice core samples is much coarser than the time scale of recent increases in greenhouse gases during the past century. Major glaciations in the northern hemisphere began about 2.6 Ma and marked the start of the Quaternary Period (Gibbard and others, 2009). Paleoclimate variability during the Quater nary Period was driven by variations in orbital forcing (Imbrie and others, 1984) and in the amount of incoming solar radia tion to the atmosphere (Berger and Loutre, 1991). Changes in 1999), rather than being the primary driver for cycles. Warm interglacial periods during the Quaternary Period might act as analogs for projected climate predictions or provide insights to the vulnerability of ecosystems to global warming. In particu lar, the penultimate interglacial period, which occurred from about 130,000 to 116,000 years ago, was likely to have been warmer than the present interglacial by as much as 3 C with less ice cover than today (Kukla and others, 2002). During the past 2,000 years, all continental areas have 0.3 C per thousand years followed by warming during the 20th century (except in Antarctica, which does not exhibit 20th century warming) [Past Global Changes (PAGES) 2k Consortium, 2013]. Superimposed upon this cooling trend, conditions of the Medieval Climate Anomaly (also known as the Medieval Warm Period) from 950 to 1250, which was

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6 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota figure 2 Mean annual maximum air temperature Mean annual minimum air temperature Isohyet of annual precipitation—Interval 50 millimeters 0 50 KILOMETERS 25 0 10 20 MILES 0 50 KILOMETERS 25 0 10 20 MILESEXPLANATIONWeather station and identifierEdwards aquifer surface-recharge areaMadison aquifer surface-recharge areaHydrogeologic unit Hondo Isotherm of mean annual maximum air temperature—Interval 1 degree Celsius Isotherm of mean annual minimum air temperature—Interval 1 degree Celsius 103' 104' 44' 44' 43'98 99 100 31 30 29 LeadCuster station Harney Peak Hondo Boerne Rockspring 18 SW Dripping Springs 6 E Crystalline core Edwards Plateau Coastal PlainBalcones EscarpmentBlack HillsPlateau Limestone 103' 104' 44' 44' 43'98 99 100 31 30 29 LeadCuster station Harney Peak Hondo Boerne Rockspring 18 SW Dripping Springs 6 E Crystalline core Edwards Plateau Coastal PlainBalcones EscarpmentBlack HillsPlateau Limestone 103' 104' 44' 44' 43'98 99 100 31 30 29 LeadCuster station Harney Peak Hondo Boerne Rockspring 18 SW Dripping Springs 6 E Crystalline core Edwards Plateau Coastal PlainBalcones EscarpmentBlack HillsPlateau Limestone 011-1-2 -2-3 -3-4 -4-5-5-6-100-1 13 1314 1412121111121114 -2 -2 1 0 -7 272626282525262626 14 13 1214 151612 1311161616 13 17 28 26 Isohyets: contours of Parameter-elevation Regressions on Independent Slopes Model Output, http://www.prism.oregonstate.eduTransverse Mercator, North American Datum 1983, Elevation dataset: National Elevation Dataset (Gesch and others, 2002; Gesch, 2007) 500600550650550600350400450500500 550450Black Hills regionBalcones Escarpment region450 400 550 700 600550650800750850500750850850900 850 800 750 700 650 Annual precipitation 700650850 26 13 15 WYOMING SOUTH DAKOTA WYOMING SOUTH DAKOTA WYOMING SOUTH DAKOTA Figure 2. Isohyetal and isothermal maps for the regions of the Balcones Escarpment and Black Hills, based on annual values computed from output from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) (Daly and others, 1994, 2002) averaged for 1901 .

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Introduction 7 followed by relatively cool conditions of the Little Ice Age from 1400 to 1700 (Mann and others, 2009). The Medieval Climate Anomaly is the most recent analog to modern and future climate warmth, but it was unlikely to have been notably warmer than the current climate (Solomon and others, 2007). It has been proposed that the onset of the Little Ice Age was triggered by a period of explosive volcanism rather than large changes in orbital or solar forcing (Miller and others, that there is no globally synchronous warm or cold period that Paleoclimatic variability for central Texas has been records, speleothems, and tree rings. Most proxy studies provide insight into climate variability at millennial scales for the Pleistocene to Holocene time periods, particularly around the last glacial period. The last glacial period in central Texas was likely relatively cool [as much as 5 C cooler than modern (Toomey and others, 1993)] and wet (Coopera others, 2001). Holocene climate generally has been charac terized as warming and drying throughout, accompanied by the Gulf of Mexico, the dominant moisture source to central Texas, also likely affected regional climate, resulting in cooler few climate studies for central Texas provide higher resolution (centennial or decadal) paleoclimatic proxies for the Holo cene. Tree-ring studies have reconstructed drought cycles for central Texas since 1500 and indicate that extended (decadal or longer) droughts that exceeded the 1950s drought in length or intensity occurred throughout the study period (Cleaveland and others, 2011). The sensitivity of the Great Plains to climate change is indicated by geologic evidence from the Holocene Epoch and by historical accounts such as the effects of the “Dust Bowl” of the 1930s on the landscape and on climate of the Midwest. Before the Dust Bowl, accounts from explorers indicate that dunes in the northern and central Great Plains might have been active in the 1800s with sources of sands being wide, sandy rivers that frequently were dry (Muhs and Holliday, 1995). 9,600 to 6,500 years before present (YBP), and episodes of dune activity from 4,500 to 2,300 YBP and 1,000 to 700 YBP (Medieval Climate Anomaly) might have occurred in response to frequent and severe drought (Miao and others, 2007). Similar periods of climate change are indicated by pollen and diatoms that are preserved in sediment cores from Moon Lake, figure 3 20 0 0 40 0 60 0 80 0 1,0 00 1,2 00 1,4 00 1,6 00 1,8 00 2,0 00 10 0 0 20 0 30 0 40 0 50 0 60 0 70 0 80 0 90 0 1,0 00 0 50 , 0 00 10 0, 000 15 0, 000 20 0, 000 25 0, 000 30 0, 000 35 0, 000 40 0, 000 45 0, 000C a rb o n d io xid e ( C O2) co n ce n t ratio n , in p a rt s p e r m illio n ( ppm ) Methane ( C H4) co n ce n t ratio n , in p a rt s p e r b illio n ( ppb ) Years before present Approximate 2013 CH4 concentration (1,800 ppb) Approximate 2050 CO2 concentration (532 ppm; A2 emission scenario) Approximate 2013 CO2 concentration (393 ppm)EXPLANATIONCO2 in ice core CH4 in ice core Figure 3. C oncentrations of greenhouse gases on the basis of the Vostok ice core, and current (2013) and projected concentrations (Petit and others, 1999; National Climatic Data Center, 2013).

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8 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota a small, closed-basin lake in the glaciated terrane of eastern salinity using diatom assemblages at Moon Lake, and the results indicate a transition from an open freshwater lake to a closed saline lake between 10,000 to 7,300 YBP, as vegetation shifted from spruce forests to deciduous parkland to prairie, and a high-salinity lake associated with drier climatic condi tions from 4,700 to 2,200 YBP. Studies of tree-ring records in averaging 12.9 years long, between 1539 and 1939 (Weakly, 1943). Periods between droughts were, on average, 20.6 years long. Much of this time period was within the relatively cool conditions of the Little Ice Age. A study of forest structure in the Black Hills noted a coincident pluvial (wet) period occur ring from the late 1700s to early 1800s, following an intense 10-year drought around 1750 (Brown, 2006). Ecological Setting The Balcones Escarpment comprises one of the most vancy, 2008) with unique, relict, and endemic terrestrial, This diversity is driven in part by local and regional climatic 1931). About 200 endemic aquatic species and 9 endemic terres trial plant species are associated with the canyons and springs of the Balcones Escarpment (supplemental table S1). In addition to surface-dwelling species, the Balcones Escarpment has a rich stygobitic fauna, with 42 described species (Hershler and The Edwards aquifer surface-recharge area along the Protection Agency Level IV ecoregions and represents 4 of the 12 Level III ecoregions in Texas: Cross Timbers (ecoregion 29), Edwards Plateau (ecoregion 30), Southern Texas Plains (ecoregion 31), and Texas Blackland Prairies (ecoregion 32) of the aquifer and much of the recharge zone lie within the Balcones Canyonlands (Level IV ecoregion 30c), an area of highly dissected limestone outcrops that forms the southern edge of the Edwards Plateau. The upland vegetation in this ecoregion predominately is woodland and park (Bezanson, 2000), and is dominated by plateau live oak [ Quercus fusi formis Juniperus ashei ), cedar elm ( Ulmus crassifolia ), and Texas oak ( Quercus buck leyi rivers and streams that support cool, moist microclimates on north-facing slopes. Vegetation in the canyons varies across local moisture gradients, from riparian forests along the stream corridors to mesic (having moderate or well-balanced supply of water) north-slope deciduous forests to drier evergreen others, 2004). The seeps and springs of the limestone canyons support endemic, rare, and relict plant species (Amos and eastern deciduous species occur within the Balcones Canyon include relicts of eastern swamp communities, such as Ameri can sycamore ( Platanus occidentalis ), black willow ( Salix nigra ), and bald cypress ( Taxodium distichum ), that occur 1988). Precipitation declines from east to west across the vegetation in the western parts of the ecoregion including Acacia sp., honey mesquite ( Prosopis glandulosa ), and cenizo ( Leucophyllum frutescens others, 2004). In these dry western regions, more mesic species associated with the plateau live oak woodland are restricted to Although most of the Balcones Escarpment lies within the Balcones Canyonlands ecoregion (ecoregion 30c), a small Texas-Tamaulipan Thorn Scrub ecoregion (ecoregion 31c) characterized by subtropical climate with hot, dry summers and mild winters. Precipitation occurs erratically and predomi nantly in spring and fall. Dominant vegetation along the south western edge of the Balcones Escarpment includes guajillo ( Senegalia berlandieri ), cenizo ( Leucophyllum frutescens ), and honey mesquite ( Prosopis glandulosa ). with the Balcones Canyonlands at the southern edge of the Balcones Escarpment. The physiography of this ecoregion is Canyonlands across the Balcones Escarpment and also from vegetation types include mesquite/live oak/bluewood ( Conda lia hookeri ) parks to the north with mesquite/granjeno ( Celtis pallida ) parks and mesquite/blackbrush ( Acacia rigidula ) and includes Comal Springs and Barton Springs. This area is named after the “black waxy” shrink-swell clays that were historically dominated by tallgrass prairie species, includ ing little bluestem ( Schizachyrium scoparium ), big bluestem ( Andropogon gerardii ), yellow indian-grass ( Sorghastrum nutans ), and tall dropseed ( Sporobolus compositus ) (Diamond is under heavy cultivation and urbanization, but some existing

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Introduction 9 figure 4 98 99100 30a 30a 27j 29e 30a 30a 30b 30c 30c 30c 30c 30d 31a 31b 31c 31c 27j 31c 32a 32a 32a 32b 33b55055050060060065065070070032c 33b 33f750750800800800850850900750750850850850800700National Land Cover data from Multi-Resolution Land Characteristics Consortium, 2011 Isohyets: contours of Parameter-elevation Regressions on Independent Slopes Model Output, http://www.prism.oregonstate.edu31 30 29Barton Springs Bexar County Index Well Comal Springs 0 50 KILOMETERS 25 0 10 20 MILESBase from U.S. Geological Survey data Transverse Mercator North American Datum of 1983EXPLANATIONOpen water National Land Cover class Level IV ecoregion boundary Developed, open space Developed, low intensity Developed, medium intensity Developed, high intensity Barren land (rock/sand/clay) Deciduous forest Evergreen forest Edwards aquifer surface-recharge area Edwards aquifer below land surface—Confined Mixed forest Limestone Plains29eLimestone Cut Plain 30aEdwards Plateau Woodland30bLlano Uplift30cBalcones Canyonlands30dSemiarid Edwards Plateau31aNorthern Nueces Alluvial Plains31bSemiarid Edwards Bajada31cTexas-Tamaulipan Thorn Scrub32aNorthern Blackland Prairie32bSouthern Blackland/Fayette Prairie32cFloodplains and Low Terraces33bSouthern Post Oak Savanna33fFloodplains and Low Terraces Shrub/scrub Grassland/herbaceous Pasture/hay Cultivated crops Woody wetlands Emergent herbaceous wetlands 550Spring or spring complex and identifier Well and identifier Level IV ecoregion identifierComal Springs Bexar County Index WellIsohyet of annual precipitation, 1901—Interval 50 millimeters Level IV ecoregion data from U.S. Environmental Protection Agency, 2011 Figure 4. E coregions and land cover of Edwards aquifer sites and the surrounding region .

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10 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota mesquite/live oak/bluewood parks occur in the northwest corner of the region and silver bluestem [ Bothriochloa laguroides Nassella leucotricha ) grasslands occur in the far northeastern end of the by pecan ( Carya illinoinensis ), eastern cottonwood ( Populus deltoides ), elm ( Ulmus spp.), ash ( Fraxinus spp.), sugar hack berry ( Celtis laevigata ), Shumard’s oak ( Quercus shumardii ), and bur oak ( Quercus macrocarpa ). The Black Hills ecological setting is “a forested island in name Black Hills comes from the contrast between the dark ponderosa pine ( Pinus ponderosa ) dominated forest character istic of the Black Hills and the lighter colored grasslands of the surrounding Great Plains. The Black Hills lie within the Middle The three Level IV ecoregions comprised by the Black Hills are related to climate patterns and topographic setting, which are associated with the geologic setting (Bryce and rates the foothills from the surrounding plains. The climate, warmer and drier than in other parts of the Black Hills, and the open ponderosa pine woodlands interspersed with mixed-grass (ecoregion 17b) is in the mid altitudes of the Black Hills and and lower altitude parts of the Limestone Plateau and the crystalline core. The Black Hills Core Highlands (ecoregion 17c) includes the highest altitude parts of the crystalline core and Limestone Plateau and are characterized by cooler temperatures and higher precipitation than other parts of the Black Hills. Although ponderosa pine forest predominates throughout the Black Hills Plateau and Black Hills Core Highlands, extremely variable topography, from broad ridges and entrenched canyons to highly dissected, tilted rock faces, produces a variety of ecological communities (Larson and The greatest concentrations of biological diversity in the Black Hills commonly are associated with surface water. All originating in the crystalline core (Driscoll and Carter, 2001), requiring more mesic, and sometimes cooler, conditions than are available in most of the Black Hills. In these areas, deciduous hardwood trees and shrubs such as box elder ( Acer negundo ), green ash ( Fraxinus pennsylvanica ), American elm ( Ulmus americana ), birch ( Betula spp.), eastern cottonwood ( Populus deltoides ), willow ( Salix spp.), dogwood ( Cornus spp.), and chokecherry ( Prunus virginiana ) are most abundant and combine into riparian forest and shrubland communities characterized by sedges ( Carex and Eleocharis spp.), bulrushes ( Scirpus and Schoenoplectus spp.), rushes ( Juncus and Luzula spp.), cattails ( Typha spp.), and some grasses (Poaceae) occur in small areas around surface water as well. With time, and shaded valleys provide special habitat required by a few disjunct species such as green spleenwort ( Asplenium tricho manes-ramosum are an example of this type of habitat. The ecological communities of the Black Hills are Basin sagebrush shrublands, and southwest deserts (McIntosh, region, the species that compose these communities are not unique. The Black Hills host isolated populations, varieties, or subspecies of some organisms (and some taxa are understud ied), but endemism at the species level is considered rare to nonexistent. In addition, the caves of the Madison Limestone generally are dry, and therefore provide little habitat for the types of unique species that inhabit caves of the Balcones for the Black Hills (Culver and others, 2003), which likely and others, 2000), because geologic exploration of the caves ter (groundwater obligate). Methods and Models Given the complexity of karst aquifers, innovative methods were required to model and evaluate their hydrologic response to projected climate change, information critical for assessing the vulnerability of associated species to climate ings to local-scale responses of aquifers and vulnerability of species at selected sites. Existing records of daily air tempera ture used to establish a time series of historical climate trends and

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Methods and Models 11 figure 5 103' 104' 44' 44' 43' Black Hills National Forest boundary Rhoads Fork Spring streamgage Spearfish Creek streamgage 43g 43g 43g 43g 43w 17c 17c 17c 17b 17a 17a 17a 17a 17a 17b350400450500 450 400 600550550500500550450650650650 700700750700500550650500450 550600450 Spearfish CreekRapid Creek 17aOpen water National Land Cover class Level IV ecoregion boundary Developed, open space Developed, low intensity Developed, medium intensity Developed, high intensity Barren land (rock/sand/clay) Deciduous forest Evergreen forest Madison aquifer surface-recharge area Mixed forest Black Hills Foothills17bBlack Hills Plateau17cBlack Hills Core Highlands43gSemiarid Pierre Shale Plains43wPowder River Basin Shrub/scrub Grassland/herbaceous Pasture/hay Cultivated crops Woody wetlands Emergent herbaceous wetlands 450Level IV ecoregion identifier Isohyet of annual precipitation, 1901–2000 —Interval 50 millimetersBase from U.S. Geological Survey data Transverse Mercator North American Datum of 1983 Level IV ecoregion data from U.S. Environmental Protection Agency, 2011National Land Cover data from Multi-Resolution Land Characteristics Consortium, 2011 0 50 KILOMETERS 25 0 10 20 MILESEXPLANATIONRed Valley Red Valley 600WYOMING SOUTH DAKOTA Figure 5. E coregions and land cover of Madison aquifer sites and the surrounding region .

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12 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota from the CCSM3 was adapted to provide initial and bound grid points nearest the location of weather stations was used to project air temperature and precipitation daily time series from 2011 to 2050. Hydrologic response to climate, histori model, a versatile time-series model that simulates waterrecords of daily precipitation and air temperature as model available at http://sd.water.usgs.gov/projects/RRAWFLOW/ RRAWFLOW.html . The superposed responses of quick and example, Pinault and others, 2001) can be simulated by the and Madison aquifer sites to changes in climate was assessed using the CCVI. The CCVI requires the user to estimate scores for factors, several of which are associated with climatic Scores for factors are based on monthly and annual trends in climate variables, and other climate metrics such as frequency of climate events and exceedances of species tolerances to climate change (supplemental table S1). Weather Station Data Historical and projected (from the start of weather station record through 2050) daily air temperature and Escarpment (Long and Mahler, 2013). Each Edwards and Madison aquifer site was assigned a primary weather station for estimates of daily air temperature and precipitation at the site (table 1), such as the Lead, South Dakota, weather station figure 6 Weather Research and Forecasting (WRF) m o d e l C o mmunit y C lim a t e S y s t e m s M o d e l, v e r s io n 3 . 0 (CCSM 3 ) o u t put : 2011–50 ( A 2 emission sc e n ar io ) d aily air t e m p e r a t u r e and p r e c ip it a t io n Climate Change Vulnerability Index (CCVI) WRF model output: 2011–50 ( A 2 emission sc e n ar io ) daily air t e m p e r a t u r e and p r e c ip it a t io n National Oceanic and Atmospheric Administration weather station records of daily air temperature and precipitation Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model RRAWFLOW model output: groundwater level, spring discharge, stream base flow Streamflow and groundwater records at U.S. Geological Survey streamgages and wells C lim a t e m o d e l p r o je c t i o n s and w e a t h e r s t a t i o n r e c o r d s Hy d r o l o gi c m o d e l Species vulnerability assessmentE X P L AN A T I O N Input data to model Output from model Linkage of data, models, and model output Model Figure 6. L inkage of model components . The final linkage is to the Climate Change Vulnerability Index for selected species.

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Methods and Models 13 Table 1. Weather stations used to synthesize climate records for the five Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model sites and weather station period of records . IDW, inverse-distance weighting interpolation method] Name of modeled site USGS site number Primary NOAA weather station Start of simulation period End of observation record a Station name Station number Latitude (NAD83DD) Longitude (NAD83DD) Madison aquifer sites 06408700 IDW of nine weather stations b ( b ) 44.125 b -103.8971 b 06/05/1920 12/29/2011 06430900 Lead, South Dakota 394834 44.3533 -103.7713 12/25/1917 12/31/2010 Edwards aquifer sites Bexar County Index Well 292618099165901 Hondo, Texas 414254 29.3364 -99.1384 09/24/1930 12/31/2010 Barton Springs 08155500 Dripping Springs 6E, Texas 412585 30.2133 -97.9822 11/05/1941 04/30/2011 Comal Springs 08168710 417712 29.7889 -100.425 11/26/1905 12/31/2010 a 12/31/2010 for all sites. b records from nearby weather stations, with weights assigned based on the distance to the primary weather station (Long and Mahler, 2013). A nearby weather station was not avail ture and precipitation were interpolated for the center of the watershed using inverse distance weights applied to records from nine surrounding weather stations, which were located within 17 kilometers (km) of the center of the watershed (Long and Mahler, 2013). Interpolated estimates of weather monthly and annual statistics, and metrics of climate vari ability for the CCVI assessments: the Boerne weather station in Texas (1906), and the Custer (1943) and the CCVI assessment, and are reported in supplemental table S1. The breadth of statistics and metrics computed (interpolated) because it was a completely synthetic record. Climate Models and precipitation through 2050 on the basis of the A2 emis sion scenario. Emission scenarios are described by the Special Swart, 2000) and the Intergovernmental Panel on Climate 2007). The A2 emission scenario represents a world that emphasizes the importance of economy (“A” scenario) over the environment (“B” scenario), with more regional responses (” scenario) than global cooperation (” scenario). In contrast to the A2 emission scenario, the A1 emission scenario represents a world with more global cooperation, and is further nonfossil-fuel intensive because of changes in technology (A1T), and a balance across available energy sources (A1B). 2 concentration for the A2 emission scenario matches the trend for the A1B scenario through 2050, with both emission scenarios attaining 2050 for other greenhouse gas emissions differ between the A2 2 concentrations from 2050 diverge for the A2 and A1B 2 emission scenarios: 567 ppmv. The A2 emission scenario was chosen for this study to align with regional climate model simulations as published by resolution based on the A2 emission scenario are available Table 2. Description and location for weather stations used to quantify climate variability . NOAA weather station Station number Location (NAD83DD) Start of record Latitude Longitude Boerne, Texas 410902 29.7986 -98.7353 1/1/1906 Custer, South Dakota 392087 43.7744 -103.6119 1/1/1943 Lead, South Dakota 394834 44.3533 -103.7713 1/1/1918

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14 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota Program ( http://www.narccap.ucar.edu ). Simulations span 1971 (contemporary climate) and 2041 (projected climate), and are driven by boundary conditions from several 1968, 2040, and 2010, and boundary conditions scenario also was chosen because observed trends in atmo 2 emissions generally have followed the trend of Murray and Hansen, 2013). As previously described, the mean 2 concentration surpassed 400 ppmv in 2013 emission scenario assume 400 ppmv for 2013. Community Climate System Model described by Collins and others (2004). Gridded output from CCSM3 is available at ~1.4-arc-degree grid spacing and a 6-hour time step for 1870, and model output can be http:// www.earthsystemgrid.org ). Although model output is reported CCSM3 are not constrained to precisely match historical weather patterns from year to year. This is what distinguishes Table 3. Dynamical mesoscale models for North American climate and associated Atmosphere-Ocean General Circulation Model (AOGCM). Source Mesoscale model AOGCM boundary conditions Time span Resolution Community Climate System Model, version 3 (CCSM3) 1971, 2041 50 km Canadian Climate Centre GCM, version 3.1/T63 (CGCM3) 1971, 2041 50 km 1971, 2041 50 km (HadCM3) 1971, 2041 50 km Mesoscale Model, version 5 (MM5) Community Climate System Model, version 3 (CCSM3) 1971, 2041 50 km Mesoscale Model, version 5 (MM5) (HadCM3) 1971, 2041 50 km Canadian Climate Centre GCM, version 3.1/T63 (CGCM3) 1971, 2041 50 km 1971, 2041 50 km Community Climate System Model, version 3 (CCSM3) 1971, 2041 50 km Canadian Climate Centre GCM, version 3.1/T63 (CGCM3) 1971, 2041 50 km Hostetler and others, 2011 Max Planck Institute, European Center for Hamburg, version 5 (MPI ECHAM5) 1968, 2040, 2010 50 km, 15 km Hostetler and others, 2011 1968, 2040, 2010 50 km, 15 km Hostetler and others, 2011 Portland State University / U.S. Geological 1968, 2040, 2010 50 km, 15 km This report Community Climate System Model, version 3 (CCSM3) 1981, 2001 36 km

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Methods and Models 15 a climate model from a weather forecast model. As such, climate modelers use the terms “pre-industrial climate” and “contemporary climate” rather than “historical climate.” A year in the late 1800s, such as 1850 or 1870, is selected to represent pre-industrial climate conditions, and is simulated ment of important hydrologic and energy budget components, such as soil moisture and soil temperature, from the conditions set for the initial time step. The CCSM3 pre-industrial climate simulation selected for this study computed the climate in 1870 for 440 annual cycles (experiment b30.020e). The CCSM3 simulation of contemporary climate is a continua tion from the pre-industrial climate simulation (annual cycle 2 concentrations from 1870 to 1999 (experiment b30.030e). This simulation commonly is referred to as the 20th Century Climate in Coupled Models (20C3M). Climate models do not use the term “future climate,” but use the term “projected climate” to recognize that greenhouse gas emissions in the future are uncertain. The CCSM3 simulation of projected climate is a continuation from the 20C3M simulation, based on an emission scenario from 2000 to 2100 (experiment b30.042e for the A2 emission scenario). The experiments selected for 20C3M and projected climate (b30.030e and b30.042e, respectively) were the only CCSM3 simulations of the A2 emission scenario for which a subdaily (6-hour) time step for model output was available. A subdaily time step, on the order of 6 hours or less, is required multiple emission scenarios, were outside the scope of this basis of the skill in simulating contemporary climate of the Great Plains during 1901. In addition to the CCSM3, the Canadian Centre for Climate Modeling and Analysis General Circulation Model, version 3.1/T63 (CGCM3) (Environment maximum air temperature were averaged to estimate monthly means of daily mean air temperature. 1901 indicate that the CCSM3 has the better skill in for all models becomes more consistent after approximately 2030. output, the CGCM3 simulated cooler climate but has the by convective precipitation systems. The CCSM3 has the because it had the best skill for simulating air temperature yet ing precipitation. Weather Research and Forecasting Model Skamarock and others, 2008), is a regional climate model and computed: 1981 (contemporary climate) and 2001 output at 3-hour intervals (computational time steps are much shorter), and were then integrated to daily and monthly time steps. Computationally similar to the atmospheric compo simulates several atmospheric variables, including tempera ture, pressure, moisture, and winds at multiple levels in the atmosphere, and hydrologic variables, including precipita tion, evapotranspiration, soil moisture, and runoff at the land surface. In the “Community Climate System Model” section, annual precipitation and air temperature for the Great Plains. of annual precipitation and air temperature for the Great is expected given that for large areas, the mean for the area would be expected to converge. Additional descriptions of are given in the “Climate Trends and Statistics” section and other sections of this report. and others, 2012). The WPS includes a program “metgrid” that inputs gridded observations of atmospheric temperature,

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16 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota figure 7 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8Air temperature, in degrees Celsius 200 400 600 800 1,000 1,200 1,400 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100Precipitation, in millimetersYearC o m m uni t y C l i m a te S y s t e m M odel , v e rs i on 3 . 0 ( C C SM3 ) G eophy s i c a l F l u i d D y nam i c s L abor a t o r y , C l i m a t e M odel 2 . 1 ( G F D L C M 2 ) C anadi an C ent r e f o r C l i m a t e M odel i ng and A nal ysi s G enera l C i rc u l a ti on M odel , v e r s i on 3 .1/T63 ( C G CM3 ) Par a m e te r -e l e v a ti on R egr e s s i ons on I ndependent S l opes M odel ( P R I S M ) EXPLANATION C o m m uni t y C l i m a te S y s t e m M odel , v e rs i on 3 . 0 ( C C SM3 ) G eophy s i c a l F l u i d D y nam i c s L abor a t o r y , C l i m a t e M odel 2 . 1 ( G F D L C M 2 ) C anadi an C ent r e f o r C l i m a t e M odel i ng and A nal ysi s G enera l C i rc u l a ti on M odel , v e r s i on 3 .1/T63 ( C G CM3 ) Par a m e te r -e l e v a ti on R egr e s s i ons on I ndependent S l opes M odel ( P R I S M ) EXPLANATION Figure 7. T ime series of annual mean surface air temperature and total precipitation during 1901 for the area of the Great Plains for three general circulation models, and during 1901 for the Parameter-elevation Regressions on Independent Slopes Model (PRISM).

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Methods and Models 17 figure 8 -1 5 -1 0 -5 0 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0A i r t e m pera tu re , i n degrees C e l s i u s 0 2 0 4 0 6 0 8 0 100 120 140 160 180 200 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.P r e c i p i ta t i on, i n m illim e t e r sMonthC o m m uni t y C l i m a te S y s t e m M odel , v e rs i on 3 . 0 ( C C SM3 ) G eophy s i c a l F l u i d D y nam i c s L abor a t o r y , C l i m a t e M odel 2 . 1 ( G F D L C M 2 ) C anadi an C ent r e f o r C l i m a t e M odel i ng and A nal ysi s G enera l C i rc u l a ti on M odel , v e r s i on 3.1/T63 ( C G CM3 ) Par a m e te r -e l e v a ti on R egr e s s i ons on I ndependent S l opes M odel ( P R I S M ) EXPLANATION C o m m uni t y C l i m a te S y s t e m M odel , v e rs i on 3 . 0 ( C C SM3 ) G eophy s i c a l F l u i d D y nam i c s L abor a t o r y , C l i m a t e M odel 2 . 1 ( G F D L C M 2 ) C anadi an C ent r e f o r C l i m a t e M odel i ng and A nal ysi s G enera l C i rc u l a ti on M odel , v e r s i on 3 .1/T63 ( C G CM3 ) Par a m e te r -e l e v a ti on R egr e s s i ons on I ndependent S l opes M odel ( P R I S M ) EXPLANATION Figure 8. M ean monthly surface air temperature and total precipitation during 1901–2012 for the area of the Great Plains for three general circulation models and for the Parameter-elevation Regressions on Independent Slopes Model (PRISM). Note that the line marking PRISM air temperature in places overlies and obscures the line for the Community Climate System Model, version 3 (CCSM3).

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18 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota figure 9 Land-surface altitude—In meters above North American Vertical Datum of 1988 2,500 0 CANADA UNITED STATES MEXICO50 40 30 20 10140 130 120 110 100 90 80 70 60 0 1,000 KILOMETERS 500 0 250 500 MILES EXPLANATIONBase from U.S. Geological Survey data Lambert Conformal Conic projection Figure 9. T he Weather Research and Forecasting (WRF) model domain extent showing land-surface altitudes at the 36-kilometer resolution .

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Methods and Models 19 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8Air temperature, in degrees Celsius 200 400 600 800 1,000 1,200 1,400 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100Precipitation, in millimetersYearC o m m uni t y C l i m a te S y s t e m M odel , v e rs i on 3 . 0 ( C C SM3 ) Par a m e te r -e l e v a ti on R egr e s s i ons on I ndependent S l opes M odel ( P R I S M ) EXPLANATION C o m m uni t y C l i m a te S y s t e m M odel , v e rs i on 3 . 0 ( C C SM3 ) Par a m e te r -e l e v a ti on R egr e s s i ons on I ndependent S l opes M odel ( P R I S M ) EXPLANATION figure 10 Weather Research and Forecasting Model (WRF) 1981– 2010 Weather Research and Forecasting Model (WRF) 2001– 50 Weather Research and Forecasting Model (WRF) 1981– 2010 Weather Research and Forecasting Model (WRF) 2001– 50 Figure 10. T ime series of annual mean surface air temperature and total precipitation for the area of the Great Plains from the Community Climate System Model, version 3 (CCSM3) , two simulations from the Weather Research and Forecasting (WRF) model (1981 and 2001) , and the Parameterelevation Regressions on Independent Slopes Model (PRISM).

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20 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota Table 4. General description of physics schemes used in the Weather Research and Forecasting (WRF) model . Physics scheme Description Physics scheme used Microphysics (WSM6) Cumulus drafts and downdrafts. Boundary layer lar importance in the lower atmosphere. Yonsei University (YSU) This part of the model adjusts the radiative properties of the atmosphere based on observed and projected atmospheric carbon dioxide concentration. Community Atmosphere Model (CAM) Surface layer momentum from the surface to the boundary layer, based on cloudiness, winds, Land surface based on results from the radiation and surface-layer schemes. Heat and mois ture from the land surface includes evaporation from the bare soil or water and from transpiration from vegetated surfaces. Soil is represented using a four-layer model with thicknesses of layers increasing downward from 100 mm, 300 mm, 600 mm to 1,000 mm, for a total soil thickness of 2,000 mm. The land surface includes a representation of soil types, land use, and seasonal vegetation “green ing.” winds, and moisture at several heights in the atmosphere and was adapted to accept input from the CCSM3, and is based on code supplied by the Mesoscale and Microscale Meteorology The adapted program, named “ccsmgrid,” also reformats soil moisture, soil temperature, sea-surface temperature, and lake temperature from the CCSM3 output. Lake temperatures were computed in ccsmgrid from the daily mean of the CCSM3 tions, such as land-surface altitude, land use, soil moisture capacity, dominant vegetation in a grid cell, monthly changes in the vegetation (greening), and albedo, were based on stan variables associated with vegetation and albedo exhibit an annual cycle. Several subgrid scale processes are represented within are referred to as “physics schemes.” The physics schemes selected for the simulation presented in this report are listed in table 4. Several of the selected physics schemes previously have been applied to weather and climate modeling in the northern Great Plains (such as Capehart and others, 2011). The radiation scheme selected is the Community Atmosphere 2 concentrations on the basis of the A2 emission scenario [other scenarios are not currently (2013) available in this radiation scheme]. The CCSM3 also uses the CAM radiation scheme. Selected physics schemes, model setup, and input data described by Wang and others (2012). The term “namelist” is “Supplement 3” section provides a glossary of terms listed in Assessment of species vulnerability required estimates of local climate from 2010, represented in this study by maximum, and minimum daily air temperature (2-m height) for grid cells that include the locations of Edwards and Madison aquifer sites and weather stations (tables 1 and 2). Bias of the mean annual air temperature and mean monthly precipitation vations during 1981. Separate bias adjustments were computed for mean, maximum, and minimum air temperature. Model bias in mean monthly precipitation was computed using both days with and without precipitation to compute mean ment was made only to days for which the model predicted a precipitation event. If bias adjustment resulted in precipitation less than 0.025 mm [the resolution of standard tipping bucket rain gages (Ahrens, 2007)], precipitation was set to zero. These steps were repeated iteratively until bias in daily mean precipi tation for the given month was less than 0.0001 mm per day.

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Methods and Models 21 precipitation, a continuous time series was constructed using weather station records through 2010 and projected through are listed in supplemental table S3. Hydrologic Model observed or projected climate data (air temperature and precipitation) as input. The model simulates two processes in series: the process of precipitation becoming recharge, and the transition of recharge into a hydrologic response. The method, described in detail in Long and Mahler (2013), is summarized in this section. Groundwater recharge was simulated using a method similar to effective-precipitation of antecedent conditions, which in turn are related to daily air temperature and daily total precipitation. Second, daily recharge was computed as the product of the daily soilmoisture index and daily precipitation. Daily precipitation tion and melting for projected periods was determined on the basis of air temperature threshold values. Third, the transition of recharge to a hydrologic response was simulated using convolution. Convolution can be used to simulate the translation of a system input into a system output that is dispersed in time according to a characteristic waveform, system output that results from an instantaneous unit input. the time that the response to the impulse effectively persists. Exponential curves, lognormal curves, or a combination Because of horizontal and vertical heterogeneity in karst, or desaturate different parts of the aquifer having different assuming time invariance within these periods. The wet and tation was greater than or less than the long-term mean, IRF w1 and IRF d1 ) IRF w2 and IRF d2 ), where the subscripts, w and d , refer to wet and dry periods, respectively. The model for each site was validated by (1) optimizing model parameters for part of the existing record of system output (calibration period), (2) executing the calibrated model for the remaining observation period using the optimized parameters (validation period), and (3) comparing the simu lated and observed outputs for the validation period. Model performance for the calibration and validation periods was ciency, E N-S 1999), which is a measure of the similarity between simulated and observed time-series records, hereafter referred to as E N-S value of zero indicates that the observed E N-S E N-S for the validation period was set at 0.70, calculated on a daily time step. calibrated and validated by using recorded (observed) mean daily air temperature and precipitation as model input, and by Information System ( http://waterdata.usgs.gov/nwis ). The validated model was then applied to historical and projected mean daily air temperature and precipitation from the nearest weather station from the start of record through 2050 to simu late a continuous record of hydrologic response. Species Assessment A large number and wide variety of species are associated with the springs, streams, and groundwater of the Edwards and Madison aquifers. Some of these species are of special conser vation concern because of their local or global rarity or factors other than (or in addition to) climate change that threaten their persistence. A list of karst-related species of conservation concern was compiled for the Balcones Escarpment and Black to meet two criteria. 1. The species is designated as at least one of the fol lowing: a. b. a sensitive species, species of local concern, or c. 2013) of 1, 2, or 3 (critically imperiled, imper iled, or vulnerable, respectively) at the global or State level (Texas for the Balcones Escarpment, and Wyoming and South Dakota for the Black d. is newly discovered and therefore not yet assigned

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22 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota 2. The species is strongly tied to karst hydrology in the region, in that at least one part of its life cycle relies heavily or exclusively on karst hydrology, or an endemic karst obligate species is dependent on it for habitat or reproduction (two species in the Balcones Escarpment), or its occurrences within the target region are wholly or largely limited to springs or streams fed by the aquifer, moist caves, the wetland or riparian areas created by these features, or the aquifer itself. the Balcones Escarpment and 25 species from the Black Hills 14 species from the Balcones Escarpment and 8 species from the Black Hills were selected for climate change vulnerability assessment because together the species span the range of broad taxonomic groups (such as mammal, bird, and plant), the species are tied to the hydrological features simulated in on the species to meet the minimum information criteria of the vulnerability assessment tool. Two plant species that did not meet these criteria, Ehretia anacua and Cabomba caroliniana , were also selected for climate change vulnerability assessment because of their importance as habitat for endangered species in the Balcones Escarpment region, resulting in a total of 16 species from the Balcones Escarpment region. A species’ vulnerability to climate change is determined by (1) the character, magnitude, and rate of changes of climatic ological, biological, and ecological factors that determine how the species is likely to be affected by the climate changes climate change effects (“adaptive capacity”) (Glick and others, 2011). The CCVI incorporates these three components (Young and others, 2012). The CCVI is programmed in a Microsoft Excel workbook, and is described by Young and others (2012). measures of direct exposure, 4 measures of indirect exposure, and 16 measures of sensitivity and adaptive capacity (table 5). Assigning more than one score indicates uncertainty. Scores categorize whether the effect of the factor decreases, somewhat decreases, does not affect, somewhat increases, increases, or the user can also assign the effect of the factor as neutral or as unknown. The direct exposure scores are used to weight scores assigned to all other factors, a weighted sum of the factors is calculated, and the weighted sum is categorized into a 5-point vulnerability index: not vulnerable/increase likely, not vulnera ble/presumed stable, moderately vulnerable, highly vulnerable, or extremely vulnerable. The not vulnerable/increase likely dance or range of the species. The not vulnerable/presumed in abundance or range of the species. This index is adjusted according to scores the user assigns to additional factors based on documented or simulated response of the species to climate change (table 5). If too many factors are scored as “unknown,” (Young and others, 2012) was used, in which 1,000 simulations were computed, each randomly selecting a single vulnerabil ity score for each factor in which more than one score was assigned. The distribution of results was used to calculate the ate, high, or very high. Supplemental table S1 provides detailed descriptions of how scores for each factor and for each species were assigned. Application of CCVI for the Balcones Escarpment and Black Hills regions varies slightly from the standard protocol protocol uses climate change values provided by Climate Wizard (available at http://www.climatewizard.org ), in which air temperature, precipitation, and aridity are compared between the historical period (1951) and the future period (2040), with the climate of the future period being a 16-model ensemble mean of the A1B emission scenario. As stated previously, the term “projected climate” rather than “future climate” is used in this report to recognize that green house gas emissions in the future are uncertain. Application of CCVI described in this report uses observed, simulated, (table 2). The “historical” and “projected” periods are rede through 1975, and 2041, respectively. Climate trends from 2011 to 2050 also are considered. Second, assessments of trends in climatic and hydro logic anomalies and indices provided information for assigning scores to two factors, C2ai and C2bi (table 5), which address the air temperature and precipitation variation, respectively, that the species has been exposed to during the 33 years prior to 1975 (table 5). In the standard proto col, the score for factor C2ai is derived as the difference between the highest mean monthly maximum air temperature and lowest mean monthly minimum air temperature for the area occupied by the species within the assessed region, and factor C2bi is derived as the maximum difference in mean annual precipitation values over the species’ range within the region. Because of the very small range (less than 100 square kilometers) of some of the species assessed in this report, these differences are not appropriate. Instead, air tempera ture variation for the species is computed as the difference ature for the historical period. Precipitation variation for the species is computed as four times the standard deviation of annual precipitation during the historical period. Third, assessment for trends in climatic and hydrologic anomalies and indices provided information for assign ing scores to three factors, C2aii, C2bii, and C2c (table 5), which address vulnerability and dependence on a disturbance regime. In the standard protocol, factors C2aii and C2bii, which respectively address the physiological thermal and

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Methods and Models 23 Table 5. Factors scored in the Climate Change Vulnerability Index (CCVI) and climate and hydrologic input used for scoring . [Differences between historical and projected are calculated as means of historical (start of record through 1975) and projected (2041) periods, whereas trends C, degrees Celsius] Factor Description Climate and hydrologic input Direct exposure A1 Air temperature change Difference between projected and historical mean annual air temperature (C). A2 Moisture metric change Percent change between projected and historical annual aridity index. Indirect exposure B1 Species’ exposure to sea level rise B2a Species’ distribution relative to natural barriers to range shift B2b Species’ distribution relative to anthropogenic barriers to range shift B3 Impact of land use change due to human re sponse to climate change Species-specific sensitivity or adaptive capacity factors C1 Species’ dispersal and movements C2ai Species’ historical thermal niche mum air temperature for historical period. C2aii Species’ physiological thermal niche Differences between historical and projected minimum and maximum air tempera tures on annual and monthly basis. Trends in annual and monthly minimum and maximum air temperatures over historical, projected, and complete periods. Dif ferences in minimum and maximum air temperature exceedance values between historical and projected periods. Difference between historical and projected periods in number of days maximum air temperature exceeds 36 C. C2bi Species’ historical hydrological niche C2bii Species’ physiological hydrological niche Differences between historical and projected annual and monthly precipita tion. Trends in annual and monthly precipitation for historical, projected, and peaks. Differences between historical and projected annual and monthly stream C2c Species’ dependence on a disturbance regime likely to be impacted by climate change Input used for C2aii and C2bii. C2d Species’ dependence on ice, ice-edge, or snowcover habitat C3 Species’ restriction to uncommon geological features or derivatives C4a Species’ dependence on other species to generate habitat and vulnerability of those species to climate change C4b Species’ dietary versatility and vulnerability of prey species to climate change (animals only) C4c Species’ pollinator versatility (plants only) C4d Species’ dependence on other species for propagule dispersal C4e interaction not covered by C4a through C4d C5a Species’ measured genetic variation

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24 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota hydrological niches of the species, are based on the percent age of the species’ occurrences or range that is restricted Vulnerability scores for these factors in this application were assigned on the basis of detailed analyses of climatological levels of dissolved oxygen are positively correlated with in Barton Springs (Mahler and Bourgeais, 2013). Dissolved oxygen sustained below 3.4 milligrams per liter for more than a month will lead to mortality of the Barton springs salamander, Eurycea sosorum (Woods and others, 2010). Adult abundance and reproduction of this salamander, which is endemic to Barton Springs, decline substantially during vulnerability scores for factors C2aii and C2bii. In another example, air temperatures above 36 C can kill the American dipper ( Cinclus mexicanus ) if the bird cannot cool itself in water (Anderson, 2002). This is a species of concern in the Black Hills region, but not the Balcones Escarpment region. Therefore, the number of days per year with maximum air temperatures exceeding 36 C was compared between historical and projected periods for the appropriate weather and hydrological information used to score these factors and factor C2c (species’ dependence on a disturbance regime) include anomalies and trends in air temperature, precipita climate change effects on various stages of the species’ life exposure by one-third for obligate cave and groundwater species under the assumption that their habitat is buffered from to respond rapidly to climate change (Loiciga and others, thus quickly affect the associated obligate cave and ground water species. Therefore, the obligate groundwater species (stygobites) from the Balcones Escarpment were not designated as buffered from local climate changes, and the reduction of exposure by one-third was not applied to the CCVI scores. Historical and Projected Climate and Hydrologic Response Historical and projected climate and hydrologic response are described to characterize climate at Edwards and Madison climate and hydrologic statistics required for CCVI to estimate species vulnerability. Climate variables for all weather stations records of total precipitation ( P ) and mean air temperature ( T mean ). Daily records of maximum air temperature ( T max ) and minimum air temperature ( T min ) for the Boerne, Custer, and Lead weather stations also were used for other analyses. Daily records were used to compute monthly and annual means or totals. A mean or total for a single year is referred to as Factor Description Climate and hydrologic input Species-specific sensitivity or adaptive capacity factors—Continued C5b last 500 years C6 Phenological response to changing seasonal air or water temperature or precipitation dynamics Documented or simulated response to climate change D1 Documented response of species to climate change D2 Modeled future change in species’ range or population size due to climate change D3 modern range D4 distribution Table 5. Factors scored in the Climate Change Vulnerability Index (CCVI) and climate and hydrologic input used for scoring .— Continued [Differences between historical and projected are calculated as means of historical (start of record through 1975) and projected (2041) periods, whereas C, degrees Celsius]

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Historical and Projected Climate and Hydrologic Response 25 the mean of all daily maximum air-temperature records ( T max ) for a single year is referred to as “annual mean T max .” Similar terminology is used for means and totals for a single month: “monthly mean” and “monthly total.” An average of annual means or annual totals over several years will be referred to as “mean annual.” Similarly, an average of monthly means or monthly totals over several years will be referred to as “mean total precipitation ( P ) will be referred to as “mean annual P .” Similarly, the mean of several years of annual mean T max would be referred to as “mean annual T max .” Projected climate variables for 2011 were simulated P, T mean , T max , T min for these years are implicitly “simulated P ,” “simulated T mean ,” “simulated T max ,” and “simulated T min “simulated water-table level.” Climate Trends and Statistics Climate trends were analyzed at Boerne, Custer, and weather stations were selected because they had the longest weather records in their respective regions. Because the Lead weather station is located in the northern Black Hills, the Custer weather station was added to characterize climate for 1943, and 1918 for the Boerne, Custer, and Lead weather stations, respectively, and these dates are referred to as “start of but were not used because records did not span a full calendar To provide consistency in trend analysis among weather stations, trends were considered starting in the year where continuous records are available for all three stations: 1943– 2050. Trends also were considered for two subset periods: 1943 (historical) and 2011 (projected). Mean annual P, T mean , T max , and T min were computed for 1943, station records from 1943, mean annual T mean , T max , and T min at the Boerne weather station is ~11 to 14 C warmer than at the Custer and Lead weather stations, and mean annual P at the Boerne weather station is ~400 and ~160 mm greater than at the Custer and Lead weather stations, respectively. Mean annual T mean , T max , and T min for the Custer weather station are within 1 to 3 C of respective means for the Lead weather station, but mean annual P for 1943 at the Custer the variability in precipitation in the Black Hills. The Kendall-tau nonparametric test (Kendall, 1938) series of annual total P , and annual mean T mean , T max , and T min ( p (rejecting null hypothesis when true) for the null hypothesis: no trend (tau=0). P , but T mean , T max , and T min (table 7). Upward trends in annual total P the time series over 1943, the Custer and Lead weather P . In contrast to the Lead weather station, the Custer weather station T mean , T max , and T min . trends in time series of annual mean T mean , T max , and T min were downward trend in time series of annual total P at the Boerne annual total P for the Lead and Custer weather stations. upward trends in time series of annual mean T mean , T max , and T min of annual P for 1943 at the Boerne weather station, Table 6. Mean annual precipitation and air temperature (daily mean, maximum, and minimum) for years 1943, 1943, and 2011 for selected weather stations . NOAA weather station 1943 1943 2011 Mean annual precipitation ( P ), in millimeters Boerne, Texas 922 892 974 Custer, South Dakota 504 484 539 Lead, South Dakota 758 730 807 Mean annual of daily mean air temperature ( T mean ), in degrees Celsius Boerne, Texas 19.1 18.7 19.7 Custer, South Dakota 6.8 6.0 8.2 Lead, South Dakota 7.6 7.0 8.5 Mean annual of daily maximum air temperature ( T max ), in degrees Celsius Boerne, Texas 25.9 25.5 26.5 Custer, South Dakota 13.9 13.4 14.7 Lead, South Dakota 13.3 12.8 14.2 Mean annual of daily minimum air temperature ( T min ), in degrees Celsius Boerne, Texas 12.2 11.9 12.9 Custer, South Dakota -0.6 -1.7 1.3 Lead, South Dakota 1.6 1.0 2.6

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26 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota figure 11 B oerne, Tex a s L ead, S outh D a k o ta C u s te r , S out h D a k o t a 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050Year 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 5 0 5 1 0 1 5 2 0 2 5 3 0 3 5 Air tem per a t ure , in degrees Celsius Mean annual daily maximum Mean annual daily mean Mean annual daily minimum 10-year moving mean of daily maximum Air temperature 10-year moving mean of annual total Precipitation 10-year moving mean of daily mean 10-year moving mean of daily minimum 0 2 0 0 4 0 0 6 0 0 8 0 0 1,0 0 0 1,2 0 0 1,4 0 0 1,6 0 0 1,8 0 0 2,0 0 01900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2011 2011 2011 2011 2011 2011 2020 2030 2040 2050 Precipitation, in millimeters Annual total EXPLANATION Figure 11. A nnual total precipitation, annual mean daily air temperatures (mean, maximum, minimum) , and 10-year moving means of annual values of weather station records (1943) and adjusted output from the Weather Research and Forecasting Model (2011) for selected weather stations .

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Historical and Projected Climate and Hydrologic Response 27 trends were indicated in time series of annual total P for 1943 at the Custer and Lead weather stations. While trends for 1943 and 2011 were upward, they 0.06 probability. The distribution of monthly precipitation and air tempera ture during a year is distinct for different climate settings of the Balcones Escarpment and the Black Hills regions. P for 1943 at the Boerne weather station had a bimodal distribution with peaks in P for 1943 at the Custer and Lead weather stations had a unimodal to weakly bimodal distribution, respectively. Mean monthly P for 2011 at the Boerne weather station has a more complex, but overall bimodal distribution, with peaks P 2011 was 46 mm greater than for 1943 (table 8). The distribution of mean monthly P for the Custer weather station for 2011 is similar to that for 19431 with increases in late summer and early autumn P The weakly bimodal distribution of mean monthly P for the Lead weather station becomes more strongly bimodal for P relative to that for 1943. The distribution of mean monthly T max and T min for the Boerne, Custer, and Lead weather stations indicates a general upward shift in air temperature from 1943 to 2011 increases of about 4.9 C (anomaly for mean monthly T max in May at the Lead weather station) and decreases of as much as 1.1 C (anomalies for mean monthly T max Custer weather station and in December at the Boerne weather station) (table 8). Climate and Hydrologic Response The hydrologic response to climate was based on appli Bexar County Index Well, for which output was water-table level in meters. Periods used for calibration and validation of described by Long and Mahler (2013), and include records from 2011 for some stations (table 1). Starting date of simula tions differs among modeled sites (table 1), and simulations based on observations extend to December 31, 2010. The tion periods indicate a good match between simulated response Table 7. Results of Kendall-tau nonparametric test of significance of trends for records and climate projections for selected weather stations . p values in bold p -value less than or equal to 0.05)] NOAA weather station 1943 1943 2011 Tau p -value Tau p -value Tau p -value Annual total precipitation ( P ) Boerne, Texas 0.114 0.081 0.179 0.031 -0.303 0.006 Custer, South Dakota 0.183 0.005 0.158 0.057 0.059 0.602 Lead, South Dakota 0.233 0.000 0.131 0.114 0.185 0.096 Annual mean of daily mean air temperature ( T mean ) Boerne, Texas 0.398 0.000 0.007 0.928 0.457 0.000 Custer, South Dakota 0.649 0.000 0.508 0.000 0.361 0.001 Lead, South Dakota 0.438 0.000 0.033 0.687 0.346 0.002 Annual mean of daily maximum air temperature ( T max ) Boerne, Texas 0.287 0.000 -0.033 0.695 0.403 0.000 Custer, South Dakota 0.440 0.000 0.169 0.042 0.330 0.003 Lead, South Dakota 0.394 0.000 0.001 0.987 0.314 0.004 Annual mean of daily minimum air temperature ( T min ) Boerne, Texas 0.446 0.000 0.069 0.409 0.414 0.000 Custer, South Dakota 0.704 0.000 0.641 0.000 0.365 0.001 Lead, South Dakota 0.470 0.000 0.080 0.335 0.393 0.000

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28 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota 0 figure 12 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 1943 mean precipitation 2011 mean precipitationEXPLANATION 1943 mean maximum air temperature 1943 mean minimum air temperature 2011 mean maximum air temperature 2011 mean minimum air temperatureEXPLANATIONB oerne, Tex a s L ead, S outh D a k o ta C u s te r , S out h D a k o t a Month -15 -10 -5 0 5 2 0 15 20 25 30 35 40Air tem per a t ure , in degrees Celsius 20 40 60 80 100 140 120 180 160Precipitation, in millimeters Figure 12. M ean monthly precipitation and air temperature (daily maximum and minimum) of weather station records (1943) and adjusted output from the Weather Research and Forecasting (WRF) model (2011) for selected weather stations .

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Historical and Projected Climate and Hydrologic Response 29 and observation records, as described by Long and Mahler given weather station records of air temperature and precipitation used for calibration and validation. Projected hydrologic response through 2050 requires input of T mean and P , as projected by the Comal Springs indicate the effect of precipitation on simu in the 1950s was matched by distinct lows in Comal Springs (2011) for this site, but annual mean water-table level of the Bexar County Index Well, below that observed in the 1950s (192.7 m in 1956), is projected for simulation years table level during a historical baseline period are compared site for which the hydrograph indicates little variability in Baseline and Projected Climate and Hydrologic Response Climate trends for historical and projected climate have been described in the context of comparison of weather station sites was not required. Therefore, weather station observa tions preceding 1943 were used, if available, through 1975. Anomalies were computed as values for 2041 minus the and duration of daily events, and annual aridity indices for the Boerne, Custer, and Lead weather stations and associated Trends Trends in time series of monthly mean and annual mean T max and T min stations were used to generate factors used in the CCVI, such Table 8. Anomalies (mean monthly or mean annual for 2011 minus respective mean monthly or mean annual for 1943) of climate variables for selected weather stations . Month Anomalies, computed as mean monthly or mean annual for 2011 minus mean monthly or mean annual for 1943 Total precipitation ( P ) anomaly (millimeters) at NOAA weather station Mean of daily maximum air temperature ( T max ) anomaly (degrees Celsius) at NOAA weather station Mean of daily minimum air temperature ( T min ) anomaly (degrees Celsius) at NOAA weather station Boerne, Texas Custer, South Dakota Lead, South Dakota Boerne, Texas Custer, South Dakota Lead, South Dakota Boerne, Texas Custer, South Dakota Lead, South Dakota -6 -1 -1 -0.1 0.6 -0.1 1.9 3.7 0.6 5 5 -3 0.1 0.3 -0.4 1.9 2.7 -0.2 March 28 8 12 0.5 2.1 1.1 1.6 2.8 1.2 April -17 14 9 1.7 4.5 4.3 2.1 3.8 3.2 May 9 -5 1 2.4 4.7 4.9 1.3 3.8 3.8 23 -12 -14 2.6 2.5 2.8 -0.3 3.1 3.1 12 -11 7 2.6 0.9 1.0 -0.5 2.3 2.0 August -15 10 10 1.8 1.3 1.5 -0.1 3.0 2.3 September -25 20 10 1.3 1.0 1.7 1.0 3.4 2.3 46 20 32 -0.1 -1.1 -0.2 1.5 2.5 0.6 0 4 9 -0.7 0.3 0.5 0.8 3.0 1.2 December 21 3 6 -1.1 -0.7 -0.8 1.0 2.2 -0.8 Annual 82 55 78 0.9 1.4 1.4 1.0 3.0 1.6

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30 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota figure 13A C C V C V VC o m a l S p r i n g s Barton Springs Bexar County Index Well EXPLANATION0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,0001900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 P r e c i p i t a t i o n , i n m i l l i m e t e r s P r e c i p i t a t i o n , i n m i l l i m e t e r s P r e c i p i t a t i o n , i n m i l l i m e t e r s Air temperature, in degrees Celsius Air temperature, in degrees Celsius Air temperature, in degrees Celsius Water-table level, i n m e t e r s above NAVD 88 Springflow, in cubic meters per second Springflow, in cubic meters per secondY e a r Observed air te m p e r a t u r e Observed pr e c i p i t a t i o n S i m u l a t e d springflow or water-table level O b s e r v e d springflow or water-table level Calibration period Validation period Simulated air te m p e r a t u r e Simulated pr e c i p i t a t i o n C V 0 2 4 6 8 1 0 1 2 1 4 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 0 1 2 3 4 5 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 1 9 0 1 9 2 1 9 4 1 9 6 1 9 8 2 0 0 2 0 2 2 0 4 2 0 6 2 0 8 2 1 0 2 1 2 Figure 13. A nnual mean air temperature, annual total precipitation, and annual mean springflow or water-table level for Edwards and Madison aquifer sites based on observed weather station records, output from the Weather Research and Forecasting (WRF) model (simulated air temperature and precipitation) , and output from the Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model (simulated springflow or water-table level).

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Historical and Projected Climate and Hydrologic Response 31 as a species’ physiological thermal and hydrological niches (factors C2aii and C2bii) (table 5). Trends also were evalu ated for time series of monthly total and annual total P , and monthly mean and annual mean T mean , which are also used in of trends was determined on the basis of the Kendall-tau nonparametric test for monthly and annual time series. trends for all climate variables (table 9). The Lead weather station had an upward trend in annual total P upward trends in monthly total P (table 10), had upward trends in annual mean T mean , T max , and T min at all three weather stations and a downward trend in annual total P for the Boerne weather station. Upward trends in annual mean T mean , T max , and T min at the Boerne weather mean T mean , T max , and T min at the Custer and Lead weather generally in agreement with trends for 1943 (table 7). Trends differed in that the upward trend in annual P for the figure 13B C V C V Rhoads Fork Spring Spearfish Creek EXPLANATION0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,0001900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 P r e c i p i t a t i o n , i n m i l l i m e t e r s P r e c i p i t a t i o n , i n m i l l i m e t e r s Air temperature, in degrees Celsius Air temperature, in degrees Celsius Springflow, in cubic meters per second Springflow, in cubic meters per secondY e a r Observed air te m p e r a t u r e Observed pr e c i p i t a t i o n S i m u l a t e d springflow or water-table level O b s e r v e d springflow or water-table level Calibration period Validation period Simulated air te m p e r a t u r e Simulated pr e c i p i t a t i o n C V 0 0 . 1 0 . 2 0 . 3 0 . 4 0 . 5 0 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 0 1 2 3 4 5 0 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 Figure 13. Annual mean air temperature, annual total precipitation, and annual mean springflow or water-table level for Edwards and Madison aquifer sites based on observed weather station records, output from the Weather Research and Forecasting (WRF) model (simulated air temperature and precipitation), and output from the Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model (simulated springflow or water-table level).—Continued

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32 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota Table 9. Statistical significance and direction of trends in monthly and annual precipitation and air temperatures at selected weather stations for the period spanning the start of weather station records (SOR) through 1975 . p Statistic January February March April May June July August September October November December Annual Boerne, Texas NOAA weather station (1906) Total precipitation ( P ) ------------Mean of daily mean air temperature ( T mean ) -----------Mean of daily maximum air temperature ( T max ) ------------Mean of daily minimum air temperature ( T min ) ------------Custer, South Dakota NOAA weather station (1943) Total precipitation ( P ) -------------Mean of daily mean air temperature ( T mean ) -------------Mean of daily maximum air temperature ( T max ) -------------Mean of daily minimum air temperature ( T min ) -------------Lead, South Dakota NOAA weather station (1918) Total precipitation ( P ) --------Mean of daily mean air temperature ( T mean ) -------------Mean of daily maximum air temperature ( T max ) -------------Mean of daily minimum air temperature ( T min ) --------------

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Historical and Projected Climate and Hydrologic Response 33 Table 10. Statistical significance and direction of trends in projected monthly and annual precipitation and air temperatures at selected weather stations for 2011 . p Statistic January February March April May June July August September October November December Annual Boerne, Texas NOAA weather station (2011) Total precipitation ( P ) ---------Mean of daily mean air temperature ( T mean ) -----Mean of daily maximum air temperature ( T max ) ------Mean of daily minimum air temperature ( T min ) ------Custer, South Dakota NOAA weather station (2011) Total precipitation ( P ) -------------Mean of daily mean air temperature ( T mean ) ----------Mean of daily maximum air temperature ( T max ) ---------Mean of daily minimum air temperature ( T min ) ---------Lead, South Dakota NOAA weather station (2011) Total precipitation ( P ) -------------Mean of daily mean air temperature ( T mean ) ----------Mean of daily maximum air temperature ( T max ) ---------Mean of daily minimum air temperature ( T min ) ---------

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34 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota Table 11. Statistical significance and direction of trends in monthly and annual precipitation and air temperatures at selected weather stations for the period spanning the start of the weather station record (SOR) through 2050 . p , statistically Statistic January February March April May June July August September October November December Annual Boerne, Texas NOAA weather station (1906) Total precipitation ( P ) -------Mean of daily mean air temperature ( T mean ) -----Mean of daily maximum air temperature ( T max ) ------Mean of daily minimum air temperature ( T min ) ----Custer, South Dakota NOAA weather station (1943) Total precipitation ( P ) -------Mean of daily mean air temperature ( T mean ) Mean of daily maximum air temperature ( T max ) ---Mean of daily minimum air temperature ( T min ) Lead, South Dakota NOAA weather station (1918) Total precipitation ( P ) ---Mean of daily mean air temperature ( T mean ) -----Mean of daily maximum air temperature ( T max ) -------Mean of daily minimum air temperature ( T min ) ----

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Historical and Projected Climate and Hydrologic Response 35 Trends in annual mean T mean , T max , and T min were upward for positive anomalies in T mean , T max , and T min for 2041 relative P were upward for all weather stations, consistent with positive anomalies in mean annual P for 2041 for the Custer and Lead weather stations, but not consistent with the negative anomaly in mean annual P for the Boerne weather station (table 12). Trends in April P in annual P P for the Custer and Boerne weather stations, which was a month that typically received higher amounts of precipitation tant upward trend in annual P and Boerne weather stations. consistent between monthly and annual means for each site and downward trends in annual and monthly water-table levels (with the exception of April) were indicated for the Bexar County Index Well. Frequencies and Extremes of Events factors for physiological thermal and hydrologic niche (table 5). if 20 percent is associated with an exceedance value of 15 C, it means that air temperature exceeded 15 C for 20 percent of the record. Exceedance values were computed for P , T max , and T min for the Boerne, Lead, and Custer weather stations (table 14), and Edwards and Madison aquifer sites (table 15). Anomalies were computed as the exceedance value for 2041 minus the value entries for exceedance values for P values reported in table 14. 68, and 77 percent of the time at the Boerne, Lead, and Custer precipitation was projected 64, 63, and 76 percent of the time at the Boerne, Lead, and Custer weather stations, respectively. In summary, the number of days with zero precipitation were similar for the two periods for the Lead and Custer weather station locations, but at the Boerne weather station location 2041. Exceedance values for air temperature (table 14) indicate anomalies on the order of 1 to 3 C for the Boerne and Lead weather station locations. Anomalies for the Custer weather station location are more extreme, particularly those associated with T min , and are on the order of increases of 5 to 6 C for all categories for the percent of time exceeded. Anomalies for the Custer weather station for T max are on the order of increases of 2 to 3 C. exceeded 10 to 20 percent of the time). Exceedance values tive anomalies, for Madison aquifer sites and Barton Springs, decreases in low water-table levels for the Bexar County Index sites. The CCVI factors also were scored on the basis of extremes in precipitation and air temperature. A metric of extremes, used for Madison aquifer sites, was the number of days that maximum air temperature exceeded 36 C and the maximum number of consecutive days in a year with a mean metric of extremes, used for all sites, was computed as the T max T min (table 16). Aridity Index The aridity index for a given year is based on the ratio of annual precipitation to annual potential evapotranspiration Abrahams, 2009), and computations include monthly total P and monthly mean T mean . Monthly potential evapotranspira tion was set to zero if monthly mean T mean was less than 0 C and otherwise was computed using the method from Hamon (1961). Calculations of potential evapotranspiration required estimates of the length of day, which were computed using the methodology described by Dingman (2002). An aridity index approaching 0.0 indicates more arid conditions (annual

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36 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota Table 12. Climate anomalies, computed as mean monthly or mean annual for 20410 minus mean monthly or mean annual for start of record (SOR) through 1975 at selected weather stations . Month Anomalies, computed as mean monthly or mean annual for 2041 minus mean monthly or mean annual anomaly for start of record (SOR) through 1975 Total precipitation ( P ) anomaly (millimeters) at NOAA weather station Mean of daily mean airtemperature ( T mean ) anomaly (degrees Celsius) at NOAA weather station Mean of daily maximum airtemperature ( T max ) anomaly (degrees Celsius) at NOAA weather station Mean of daily minimum airtemperature ( T min ) anomaly (degrees Celsius) at NOAA weather station Boerne, Texas Custer, South Dakota Lead, South Dakota Boerne, Texas Custer, South Dakota Lead, South Dakota Boerne, Texas Custer, South Dakota Lead, South Dakota Boerne, Texas Custer, South Dakota Lead, South Dakota -11.7 -4.6 -6.5 1.1 5.5 3.0 0.8 2.8 2.3 1.4 7.8 3.5 1.2 5.4 6.9 1.1 4.2 2.4 0.5 2.0 1.8 1.5 6.5 3.0 March 38.8 8.9 31.3 1.4 3.4 1.4 0.9 2.7 1.4 1.9 4.2 1.4 April -24.0 20.3 16.0 2.7 6.5 5.5 2.6 6.8 6.3 2.8 6.6 5.2 May -7.8 -0.3 12.6 3.0 5.8 5.0 4.2 5.8 5.5 2.0 5.7 4.8 23.0 -19.4 -9.2 2.0 3.9 2.9 3.8 2.9 2.5 0.5 4.4 3.2 -3.2 -0.1 4.2 1.7 2.9 1.6 3.7 1.1 0.8 0.3 4.4 2.4 August -13.3 21.6 28.5 1.9 3.0 1.7 2.6 1.2 1.1 0.7 4.7 2.5 September -23.2 25.7 10.3 1.9 3.4 1.9 2.1 1.7 1.7 1.6 5.7 2.8 5.5 27.0 55.1 1.3 2.0 0.6 0.8 -0.5 0.5 1.6 4.9 1.4 0.7 5.7 17.2 1.3 3.8 2.3 1.0 1.7 2.2 1.6 5.9 2.5 December 6.6 8.9 23.0 0.5 0.9 -1.3 0.0 -1.7 -1.4 1.0 3.1 -1.4 Annual -7.6 99.1 189.3 1.7 3.8 2.2 1.9 2.2 2.1 1.4 5.3 2.6

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Historical and Projected Climate and Hydrologic Response 37 Table 13. Statistical significance and direction of trends in monthly mean and annual mean springflow or water-table level at Edwards and Madison aquifer sites based on output from the Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model . p Aquifer site January February March April May June July August September October November December Annual Start of record through 1975 Comal Springs -------------Barton Springs -------------Bexar County Index Well -------------------------2011 Comal Springs Barton Springs Bexar County Index Well --------------------------Start of record through 2050 Comal Springs Barton Springs -------------Bexar County Index Well -

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38 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota precipitation approaches zero and is less than potential evapotranspiration), with wetter conditions as the aridity index approaches 1.0 (annual precipitation approaches or exceeds the value of potential evapotranspiration). Aridity index has 1. Hyperarid: less than 0.05 2. Arid: 0.05 to 0.20 3. Semiarid: 0.20 to 0.50 4. Dry-subhumid: 0.50 to 0.65 Aridity index was computed for the Boerne, Custer, and weather station is dry-subhumid, and the percentage of years Table 14. Exceedance values of daily climate variables for selected weather stations, on the basis of observational records for the start of record (SOR) through 1975 and output from the Weather Research and Forecasting (WRF) model for 2041 . exceedance value for start of weather station record through 1975] Percentage of time exceeded Boerne, Texas NOAA weather station Custer, South Dakota NOAA weather station Lead, South Dakota NOAA weather station 1906 2041 Anomaly 1943 2041 Anomaly 1918 2041 Anomaly Daily total precipitation ( P ), in millimeters 10 4.6 5.5 0.9 3.3 4.0 0.7 5.1 6.7 1.6 20 0.5 3.3 2.8 0.5 0.8 0.3 1.8 3.3 1.6 50 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 80 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 90 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Daily maximum air temperature ( T max ), in degrees Celsius 10 35.00 37.73 2.73 27.78 28.84 1.06 27.78 28.81 1.03 20 32.80 36.02 3.22 23.89 25.72 1.84 24.44 25.75 1.30 50 26.70 28.26 1.56 12.78 16.40 3.62 12.78 15.87 3.09 80 18.90 19.52 0.62 3.33 5.53 2.19 2.22 4.74 2.52 90 15.00 15.79 0.79 -1.11 0.81 1.92 -1.67 0.08 1.75 Daily minimum air temperature ( T min ), degrees Celsius 10 21.10 21.20 0.10 8.89 13.80 4.91 13.89 15.95 2.06 20 20.00 20.17 0.17 6.11 11.15 5.04 10.00 13.30 3.30 50 13.90 15.36 1.46 -2.78 2.80 5.58 1.11 4.21 3.10 80 3.90 6.63 2.73 -11.67 -5.42 6.25 -7.22 -4.33 2.89 90 0.00 2.86 2.86 -16.67 -11.79 4.88 -12.22 -10.76 1.46 the Custer weather station and decrease for the Lead weather station. The trend in aridity index for the Custer weather station for historical climate, but commonly (80 percent of years) is lower (more arid) than the Lead weather station for projected climate of 2011. Species Vulnerability to Projected Climate and Hydrologic Response Climatic and hydrologic information was used to deter the CCVI to quantify species vulnerability to climatic and model projections for the hydrological features that the species ing scores for each species evaluated are in supplemental table S1, and a summary of the results are in table 18.

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Species Vulnerability to Projected Climate and Hydrologic Response 39 Table 15. Exceedance values of simulated daily springflow or water-table level for Edwards and Madison aquifer sites based on output from Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model for the start of record (SOR) through 1975 and for 2041 . [Anomalies are computed as the exceedance value for 2041 minus the associated exceedance value for start of record through 1975] Percentage of time exceeded Edwards aquifer sites Madison aquifer sites Barton Springs springflow (cubic meters per second) Comal Springs springflow (cubic meters per second) Bexar County Index Well, water-table level (meters) Spearfish Creek springflow (cubic meters per second) Rhoads Fork Spring springflow (cubic meters per second) 1942 2041 Anomaly 1906 2041 Anomaly 1931 2041 Anomaly 1918 2041 Anomaly 1921 2041 Anomaly 10 2.473 1.257 -1.215 9.966 8.801 -1.165 205.90 196.75 -9.153 2.102 2.557 0.455 0.186 0.179 -0.008 20 2.185 1.132 -1.053 9.250 8.464 -0.785 204.55 195.84 -8.712 1.791 2.107 0.315 0.165 0.175 0.010 50 1.230 0.911 -0.319 7.711 7.692 -0.019 200.69 194.50 -6.186 1.232 1.792 0.560 0.132 0.164 0.032 80 0.781 0.781 0.000 6.192 6.536 0.344 197.18 192.60 -4.581 0.971 1.569 0.598 0.106 0.152 0.046 90 0.650 0.680 0.031 5.404 5.329 -0.075 195.27 190.87 -4.393 0.829 1.434 0.605 0.098 0.150 0.052 Species Vulnerability All of the 16 species evaluated for the Balcones Escarp ment region occurred in either Comal or Barton Springs. occurred in the springs, and two of the species were domi nant riparian relict plants (supplemental table S1). Two of the plant species in the Balcones Escarpment region, Ehretia anacua and Cabomba caroliniana , were evaluated because of their importance as habitat for two endangered species from Comal Springs, Heterelmis comalensis and Etheostoma fonti cola , respectively. However, Ehretia anacua and Cabomba caroliniana are not listed in supplemental table S1 because they are not species of conservation concern. As described in the “Species Assessment” section, the stygobites were not scored as such in the CCVI score sheet because of the rapid response of these karst systems to surface conditions. The table level across all months for 2011 (table 13). scored as highly vulnerable, four spring and riparian plants as well as two invertebrates were scored as not vulnerable/ presumed stable, and the remaining nine species were scored region, the projected air temperature increase at the Boerne weather station, as assessed by the difference between mean annual T mean between 1906 and 2041 (factor A1, period 2011, trends in mean monthly T mean were projected to have an increasing trend during 7 months whereas precipi tation was projected to decrease during 3 months (table 10). moisture index (factor A2, table 19), which is the lowest sever ity category for the CCVI. All of the species that were scored as highly or moder ately vulnerable in the Balcones Escarpment region are obligate aquatic cave or spring species in habitats that have undergone substantial historical hydrological variation of these species are affected negatively by extremely low Bexar County Index Well were invaluable for scoring vulnera bility of these species. Mean monthly precipitation is projected to decrease for only 6 months of the year, mostly during the each month for the period 2011 (table 13). In Comal

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40 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota for 1906 to 7.69 m 3 /s for 2041 (0.2 percent change), to decrease from 1.23 for 1942 to 0.91 m 3 /s for 2041 (30 percent change) (table 15). Water-table levels for the Bexar County Index Well are also projected to decrease, with median water-table levels decreasing from 200.7 for 1931 to 194.5 m for 2041, a change of 6.2 meters (table 15), with projected annual mean water-table levels falling below that observed in the 1950s (192.7 m in 1956) for simulation water-table levels led to scoring all of the Barton Springs and aquifer species as increase or greatly increase for hydrologi cal niche (factor C2bii, supplemental table S1). Due to species from this site were scored as increase to somewhat increase for hydrological niche (factor C2bii, table S1). Where data were available that linked increased water of species were narrow, those species were scored with higher Etheostoma fonticola , the endangered Service, 1974), has very narrow thermal tolerance with an ideal water temperature of 24 C, a decrease in reproduction above water temperatures of 26 C, and a critical thermal maximum water temperature of 34.8 C (Brandt and others, months, the declines were small, so this species’ vulnerability to air-temperature change was scored with some uncertainty as greatly increase or increase (factor C2aii, supplemental table S1). figure 14 0 1 2 3 4 5 6 7 8 9 10 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050N um ber of day sY ear Total days Consecutive daysEXPLANATION Figure 14. N umber of days and consecutive days in a year that the maximum daily air temperature exceeded 36 degrees Celsius at the Lead, South Dakota, weather station . (Data records begin in 1918). Table 16. Range in annual temperature measured as July mean daily maximum air temperature minus January mean daily minimum air temperature for start of weather station record (SOR) through 1975 for selected weather stations . Statistic Air temperature, in degrees Celsius (SOR) Boerne, Texas NOAA weather station Custer, South Dakota NOAA weather station Lead, South Dakota NOAA weather station Mean of maximum daily air temperature ( T max 34.0 26.7 27.1 Mean of minimum daily air temperature ( T min 2.9 -14.8 -10.0 31.1 41.6 37.1

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Species Vulnerability to Projected Climate and Hydrologic Response 41 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050Aridity indexY ear EXPLANATION Boerne, Texas Custer, South Dakota Lead, South Dakota Upper limit for dry subhumid classification Figure 15. A ridity index for start of records through 2050 for selected weather stations . Table 17. Percentage of years in listed time periods of aridity index classifications for weather stations for three periods: start of weather station record (SOR) to 1975, 2041, and SOR . tration] Years Hyperarid Arid Semiarid Dry-subhumid Wetter than drysubhumid Boerne, Texas NOAA weather station 1906 0.0 0.0 25.7 52.9 21.4 2041 0.0 0.0 10.0 70.0 20.0 1906 0.0 0.0 16.6 50.3 33.1 Custer, South Dakota NOAA weather station 1943 0.0 0.0 3.0 39.4 57.6 2041 0.0 0.0 0.0 50.0 50.0 1943 0.0 0.0 6.5 35.2 58.3 Lead, South Dakota NOAA weather station 1918 0.0 0.0 5.2 34.5 60.3 2041 0.0 0.0 0.0 20.0 80.0 1918 0.0 0.0 5.3 29.3 65.4

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42 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota Table 18. Climate change vulnerability, confidence in that assessment, and vulnerability to other anthropogenic threats (as estimated by Natural Heritage rank) for selected karst-hydrology-dependent species in the Balcones Escarpment and Black Hills regions . Assessment area Climate (hydrology) sites Major taxonomic group Taxon Climate vulnerability Confidence Natural heritage vulnerability Balcones Escarpment Boerne (Barton springs) amphibian Eurycea sosorum (Barton Springs salamander) Highly vulnerable Moderate Texas: S1 Global: G1 Balcones Escarpment Boerne (Barton springs) amphibian Eurycea waterlooensis (Austin blind salamander) Moderately vulnerable Very high Texas: S1 Global: G1 Balcones Escarpment Boerne (Bexar County Index Well) arthropod Stygobromus pecki (Peck’s Cave amphipod) Moderately vulnerable Very high Texas: S1 Global: G1G2 Balcones Escarpment Boerne (Comal Spring) arthropod Heterelmis comalensis Moderately vulnerable Very high Texas: S1 Global: G1 Balcones Escarpment Boerne (Comal Spring) Etheostoma fonticola (fountain darter) Moderately vulnerable Very high Texas: S1 Global: G1 Balcones Escarpment Boerne (Bexar County Index Well) amphibian Eurycea rathbuni (Texas blind salamander) Moderately vulnerable Moderate Texas: S1 Global: G1 Balcones Escarpment Boerne (Comal Spring) amphibian Eurycea sp. ( Eurycea sp. 8 in Springs salamander) Moderately vulnerable Moderate Texas: S1 Global: G1Q Balcones Escarpment Boerne (Bexar County Index Well) arthropod Haideoporus texanus [Edwards Aquifer diving beetle Moderately vulnerable Moderate Texas: S1 Global: G1G2 Balcones Escarpment Boerne (Bexar County Index Well) arthropod (Ezell’s Cave amphipod) Moderately vulnerable Moderate Texas: S1 Global: G2G3 Balcones Escarpment Boerne (Bexar County Index Well) arthropod Stygoparnus comalensis [Comal Springs dryopid beetle Moderately vulnerable Low Texas: S1 Global: G1G2 Balcones Escarpment Boerne (Comal Spring) vascular plant Ehretia anacua a (knockaway, anaqua) presumed stable Very high Global: G5 Balcones Escarpment Boerne (Comal Spring) vascular plant Taxodium distichum (bald cypress) presumed stable Very high Global: G5 Balcones Escarpment Boerne (Comal Spring) vascular plant Cabomba caroliniana a (Carolina fanwort) presumed stable Very high Global: G3G5 Balcones Escarpment Boerne (Barton springs) mollusk Stygopyrgus bartonensis (Barton cavesnail) presumed stable Moderate Texas: S1 Global: G1 Balcones Escarpment Boerne (Bexar County Index Well) arthropod Calathaemon holthuisi (Purgatory Cave shrimp) presumed stable Low Global: G1G2 Balcones Escarpment Boerne (Comal Spring) vascular plant Platanus occidentalis (American sycamore) presumed stable Low Global: G5

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Species Vulnerability to Projected Climate and Hydrologic Response 43 Differences in vulnerability scores among the four species of salamanders were determined by severity of the salamander ( Eurycea sosorum ) and Austin blind salamander ( Eurycea waterlooensis ), occur in Barton Springs, a highly altered spring system, with the largest of the four springs in the Barton Springs complex used as a municipal swimming pool. The spring hydrology has been substantially altered by surface dispersal among the springs. Although salamanders could potentially disperse through the karst aquifer outside of the Barton Springs complex, that has not been demon E. sosorum and E. nana (San Marcos salamander) in the als through the aquifer has yet to be demonstrated. Thus, factors relating to natural and anthropogenic dispersal barri ers (factors B2a and B2b) were scored as greatly increased for these species (supplemental table S1). These high vulnerabilities to migration coupled with high vulnerability to hydrologic niche (C2bii) resulted in the Barton Springs salamander, Eurycea sosorum , to be scored as highly vulner able, the highest vulnerability of any species in the study. Table 18. Climate change vulnerability, confidence in that assessment, and vulnerability to other anthropogenic threats (as estimated by Natural Heritage rank) for selected karst-hydrology-dependent species in the Balcones Escarpment and Black Hills regions.—Continued Assessment area Climate (hydrology) sites Major taxonomic group Taxon Climate vulnerability Confidence Natural heritage vulnerability Black Hills Creek) bird Cinclus mexicanus (American dipper) Moderately vulnerable High South Dakota: S2 Wyoming: S4 Global: G5 Black Hills Creek), Custer vascular plant (lesser yellow lady’s slipper) Moderately vulnerable High Wyoming: S2 Global: G5 Black Hills Creek), compos Spring), Custer vascular plant Equisetum scirpoides (dwarf scouringrush) Moderately vulnerable Moderate South Dakota: S2 Wyoming: S1 Global: G5 Black Hills vascular plant Salix serissima (autumn willow) Moderately vulnerable Low South Dakota: S1 Wyoming: S1 Global: G4 Black Hills Creek), compos Spring), Custer mammal Zapus hudsonius campestris (Bear Lodge meadow jumping mouse) presumed stable Very High South Dakota: S3 Wyoming: S1 Global: G5T3 Black Hills Creek) vascular plant Asplenium trichomanes-ramosum (green spleenwort) presumed stable Very High South Dakota: S2 Wyoming: S2 Global: G4 Black Hills Creek), compos Spring) mollusk Oreohelix cooperi b (Black Hills mountainsnail) presumed stable Low South Dakota: S2 Wyoming: not rated Black Hills Creek), compos Spring), Custer mammal Castor canadensis (American beaver) increase likely Low South Dakota: S5 Wyoming: S5 Global: G5 a Species was selected because of its importance in providing habitat for species of conservation concern. b Because the taxonomy of the genus Oreohelix is uncertain, O. cooperi often is not considered a species distinct from O. strigosa . We follow Weaver and others (2006) in nomenclature (that is, use O. cooperi ) and in the assumption that there is only one O. cooperi taxon in the Black Hills, as opposed to the two or

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44 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota Table 19. Climate and hydrologic input for factors in the Climate Change Vulnerability Index (CCVI) for each weather station/hydrologic site . Factor Description Climate and hydrologic input Boerne, Texas NOAA weather station/Barton and Comal Springs Custer, South Dakota NOAA weather station Lead, South Dakota NOAA weather sta tion/Spearfish Creek Synthetic a / Rhoads Fork Spring A1 Air temperature change Difference between projected and histori cal mean annual air temperature (C). 1.7 3.8 2.2 2.0 A2 Moisture metric change Percent change between projected and historical annual aridity index. 0.099 -0.069 0.047 0.049 C2ai Species’ historical thermal niche minimum air temperature for historical period (C). 31.1 41.6 37.1 C2aii Species’ physiologi cal thermal niche Differences between historical and projected minimum and maximum air temperatures on annual and monthly basis. Table 12 Table 12 Table 12 ( a ) Trends in annual and monthly minimum and maximum air temperatures for historical, projected, and complete periods. Tables 9, 10, 11 Tables 9, 10, 11 Tables 9, 10, 11 ( a ) Differences in minimum and maximum air temperature exceedance values be tween historical and projected periods. Table 14 Table 14 Table 14 ( a ) Difference between historical and project ed periods in number of days maximum air temperature exceeds 36 C. ( a ) C2bi Species’ historical hydrological niche nual precipitation over the historical period (millimeters). 1,041 343 658 424 C2bii Species’ physiologi cal hydrological niche Differences between historical and projected annual and monthly precipitation. Table 12 Table 12 Table 12 ( a ) Trends in annual and monthly precipita tion for historical, projected, and com plete periods. Tables 9, 10, 11 Tables 9, 10, 11 Tables 9, 10, 11 ( a ) (or water-table level) for historical, projected, and complete periods. Table 13 Table 13 Table 13 ( a ) Differences between historical and pro ance values, and size of peaks. ( a ) C2c Species’ dependence on a disturbance regime likely to be impacted by climate change Input used for C2aii and C2bii. ----a

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Species Vulnerability to Projected Climate and Hydrologic Response 45 In contrast, Eurycea sp. 8, which was scored by the CCVI as moderately vulnerable, occurs in Comal Springs where Barton Springs, and the spring systems are less hydrologi cally altered. ment region, American sycamore ( Platanus occidentalis ) and bald cypress ( Taxodium distichum ) are relict species at their westernmost distribution, and knockaway ( Ehretia anacua ) and Carolina fanwort ( Cabomba caroliniana ) are common aquatic plants that provide important habitat for the Comal All of the plants were scored as not vulnerable/presumed dence in the vulnerability score for P. occidentalis was low with 54.8 percent of Monte Carlo runs resulting in a score of not vulnerable/presumed stable whereas the remaining runs resulted in a score of moderately vulnerable (table S1). Previous research showed that the relict species depend on cool, moist canyons in their western distribution (Amos and moisture needs, Prasad and others (2007) suggested that a could lead to their extirpation in their far western distribution. Climate and hydrology were not simulated in this study for the far western part of the Balcones Escarpment, which receives substantially less annual precipitation than do the areas near Barton and Comal Springs. Expanding climate and hydro logic modeling to the sites in the western part of the Balcones Escarpment may therefore yield different climate vulnerability assessments for these species. All of the insects and amphipods, with the exception of Heterelmis comalensis , are stygobites that are vulnerable moderately vulnerable due to high vulnerabilities to thermal and hydrological niches (C2aii and C2bii, respectively, table S1). However, little biological information is available generally low. two were scored as not vulnerable/presumed stable and three dence (table 18). The remaining three species’ scores had between not vulnerable/presumed stable and not vulnerable/ increase likely, and two border between moderately vulnerable and not vulnerable/presumed stable), as Monte Carlo simula tions produced the two ranks with nearly equal frequency (supplemental table S1). Climate for four of the assessed Black Hills species was represented by the Lead weather station and the inter increases were moderate and precipitation increases substan tial (table 12), yielding a positive moisture metric change, as aridity index (table 19). Thus, for these species, biological factors that make them sensitive to moisture-related climate changes were generally ameliorated by low exposure to increased aridity, and biological factors that make them sensitive to heat-related climate changes were ameliorated by moderate air-temperature changes. The other four species assessed for this region have broader geographic ranges that encompass climate represented by the Custer weather station. (table 12) fell into the highest category for air-temperature change exposure in the CCVI. In addition, although projected annual precipitation was higher than for the historical period, the increase was only half of that at the Lead station (table 12). Combined, these led to a projected decrease in the moisture metric (table 19) and less amelioration for heatand moisturesensitive biological factors. Differences in exposure to projected climate changes did not fully explain differences in species’ vulnerability scores, however (table 18). Although exposed to a large mean annual T mean increase of 3.8 C, the Bear Lodge meadow jumping mouse ( Zapus hudsonius campestris ) and American beaver ( Castor canadensis ) were scored as not vulnerable to climate change (table 18) because they are not restricted by high air temperatures and have broad habitat and dietary tolerances (supplemental table S1). The green spleenwort ( Asplenium trichomanes-ramosum ), a fern at the southern edge of its range whose habitat in the Black Hills is almost exclusively on vertical limestone outcrops along not vulnerable. Its restrictive thermal tolerance and habitat are ameliorated not only by the moderate projected climate for this habitat, but also by the high mobility of its propa other species and disturbance regimes. Vulnerability scores for Black Hills mountainsnail ( Oreo helix cooperi and autumn willow ( Salix serissima ) in the Black Hills region border between not vulnerable/presumed stable and moder ately vulnerable, but for different reasons. Adaptive capacity of both was reduced by their small or isolated populations and by its high dispersal ability (wind-blown seeds), and projected mycorrhizal symbionts and the projected climate’s effect on forces put the species’ vulnerability on the border between two scores (supplemental table S1). This greater uncertainty stemmed partially from more information being available for among publications indicated different vulnerability scores

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46 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota The four most vulnerable species for the Black Hills were scored as moderately vulnerable (table 18). Adaptive capacity of the American dipper ( Cinclus mexicanus ) and dwarf scouringrush ( Equisetum scirpoides ) are hampered by their low population sizes and the lack of appropriate habitat to which they can migrate (presumably following air temper ature changes) within or near the Black Hills. Tolerance for high air temperatures was known (dipper) or presumed (scouringrush) to be low based on their physiology or current frequency of days with maximum air temperatures over a its vulnerability to overheating (Willson and Kingery, 2011). In contrast, the yellow lady’s slipper ( Cypripedium parvi ), an orchid, was vulnerable because of its reliance on other species for pollination, habitat, and sustenance (through mycorrhizal symbionts), as well as its low dispersal ability. Both of the moderately vulnerable plants were also affected by the increased aridity in portions of their range represented by the Custer climate station (supplemental table S1). The American dipper was the only Black Hills species for which the CCVI factors related to documented or simu lated response to climate change (table 5) could be scored. Vulnerability based on these factors alone also was moderately the CCVI produced similar results: medium sensitivity in the and not at risk for climate change effects in California (Gardali and others, 2012). This is the only scored species in the Black Hills for which other climate sensitivity analyses have been published. Climate change is only one of many anthropogenic threats to species, and species vulnerability to these other threats might or might not correspond well to their vulner ability to climate change. Among the 24 species assessed among both regions, the species most vulnerable to other 2013) also were more vulnerable to climate change than were other species, in that the least imperiled species were scored both moderately vulnerable and highly vulnerable to climate change. Differences Between Regions ment that met criteria for inclusion in this study, 75 percent of the species are endemic, 25 percent are aquatic obligates, and 29 percent are stygobites (supplemental table S1). Conversely, of the 25 species in the Black Hills that met the criteria for inclusion, one is endemic, one is fully aquatic, and none are stygobitic. The lack of stygobitic taxa in the Black Hills cave systems and aquifers relative to the input that supports species in the Balcones Escarpment region. Although the microbial community of the Madison aquifer is diverse and unique, this water has microbial biomass two to three orders of magnitude lower than that of any other karst environment, aquifer, or other body of water yet examined (Barton, 2012). The biota in the Black Hills region had no species that were scored as highly vulnerable, had 50 percent scored as moderately vulnerable, and 38 percent scored as not vulner able/presumed stable, whereas the Balcones Escarpment biota had 6 percent as highly vulnerable species, 56 percent as moderately vulnerable species, and 38 percent as not vulnera ble/presumed stable species. Although the scored species were not a random or even representative sample of the biota of either area, it is unlikely that the difference between these two karst regions would change if more species were assessed. The Balcones Escarpment species had higher vulnerability scores than those in the Black Hills because of their high levels of endemism and therefore highly restricted range, habitat, and, in some cases, thermal tolerances, as well as higher sever springs and well, respectively, and more uncertainty in future municipal water needs with climate change in the Balcones Escarpment region contrasts with increased median stream associated species are concentrated. Evaluation of the Approach The very detailed climate and hydrological information produced by the approach of coupling a regional climate makes it possible to evaluate some factors in much more detail than with the standard CCVI approach. The high spatial resolution of the climate projections revealed differ ences in the magnitude of air-temperature trends within the small area of the Black Hills (factor A1, table 19), which resulted in higher air temperature exposure scores for some Black Hills species than would have been assigned with more coarse climate information. This resolution is particu larly important for regions like the Black Hills and Balcones Escarpment, both of which have strong climatic gradients over relatively small distances. Detailed hydrologic response projections also affected vulnerability scores. Using only precipitation projections, the Balcones Escarpment species would have been scored in the “neutral” to “somewhat declining precipitation during the three summer months and water-table level in all three sites that were modeled in the Balcones Escarpment region (table 13). These data

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Summary 47 were key for interpreting the effect of climate change on obligate aquatic species and led to increased vulnerability scores for 12 of the 16 species assessed. Vulnerability scores for hydrologically related factors in the Balcones Escarp ment increased from “neutral” or “somewhat increase” to “somewhat increase” or “increase” for 11 of the 12 obligate aquatic species, and increased to “increase” or “greatly increase” for the Barton Springs salamander (supplemental table S1). not have been predicted solely on the basis of precipitation and air temperature data (table 12), caused vulnerability scores to be slightly lower than would have been assigned without the hydrological response information. Thus, although hydrologi cal response information was important for assessing climate change vulnerability of species in both regions, the diversity of fully aquatic species tied to individual springs in the Balcones Escarpment region made this information more critical than in the Black Hills region. A single climate projection and subsequent hydrologi cal response can yield substantially different results from climate projection in the standard protocol provided by the CCVI (Young and others, 2012) had been used, aridity changes in the Black Hills would have been in the third and fourth, and the Balcones Escarpment in the fourth, of the standard’s six aridity exposure categories (with differs from the aridity index, previously discussed in the the Black Hills in the lowest category (for more restricted species) or lowest three categories and Balcones Escarp of the CCVI-provided data for the Lead weather station, but higher for the Custer weather station and lower for the Boerne weather station. Additional climate modeling at the conditions or greenhouse gas scenarios, would allow evalu ation of the robustness of the derived species vulnerability scores. response projections were very useful for improving the assessment of karst hydrology-related species’ vulnerability to climate change, the historical data needed to accurately model hydrological response as done here do not exist for many springs and streams. Variability in the response functions of karst-fed springs and streams to contemporary climate (Long and Mahler, 2013) might preclude extrapo lating hydrologic response of one site with a long history of measurement to another with little data. Where data are available, however, this approach should improve assess ments of karst-associated species and ecosystem vulnerabil ity to climate change. Summary Karst aquifers are important groundwater resources in systems, respond rapidly to climate change. Two karst aqui fers, the Edwards aquifer in the Balcones Escarpment region of south-central Texas and the Madison aquifer in the Black Hills of western South Dakota, were evaluated for hydrologic response to projected climate change through 2050. Edwards aquifer sites include Barton Springs, the Bexar County Index Well, and Comal Springs. Madison aquifer sites include Spear were based on output from the Community Climate System projections were bias adjusted to match means for 1981 from weather station records, including those at Boerne, Texas, mean, maximum, and minimum air temperature for all weather tion for the Boerne weather station. The hydrologic response to projected climate at spring temperature and precipitation) to simulate a hydrologic response. The model simulates two processes in series: the process of precipitation becoming recharge, and the transition of recharge into a hydrologic response. Projected (2011) no trend for Madison aquifer sites. Drought equivalent to the Comal Springs (Edwards aquifer site), but a general downward projected increases in air temperature at this and other Edwards aquifer sites. Simulated annual mean water-table level of the Bexar County Index Well fell below that observed in the 1950s (192.7 meters in 1956) for simulation years 2046 and 2047. Many biological communities and ecosystems associ ated with karst aquifers and terranes are extremely sensitive to changes in hydrologic conditions. Historical and projected climate trends, computed metrics such as aridity index, and species vulnerability to projected climate based on the Climate Change Vulnerability Index. Sixteen species associated with springs and groundwater were assessed in the Balcones Escarpment region. The Barton Springs salamander ( Eurycea sosorum ) was scored as highly salamanders, a fountain darter ( Etheostoma fonticola ), three the Barton cavesnail ( Stygopyrgus bartonensis ), and a cave

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48 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota Vulnerability of eight species associated with streams Cinclus mexicanus ) and the lesser yellow lady’s slipper ( Cypripedium ) were scored as moderately vulernable with high Equisetum scirpoides ) and autumn willow ( Salix serissima ) were also scored as presumed stable or not vulnerable/increase likely. Lower vulnerability for the Black Hills species in comparison to thermal tolerance of many of the species for the Black Hills region. Importantly, climate change vulnerability scores differed substantially for Edwards aquifer species when the species depend on were included. Scores using these table level led to increased vulnerability scores for 12 of the 16 species. References Cited ogy, v. 24, p. 251. (Also available at http://dx.doi. org/10.1016/0022-1694(75)90084-0 .) Geological Society of America Annual Meeting, San Anto nio, Texas, 200 p. Ahrens, C.D., 2007, Meteorology today, An introduction to weather climate and the environment (8th ed.): Stamford, Conn., Thomson Brooks/Cole, 537 p. plus appendices. ciogenic and nonglaciogenic sources: Geological Society of America Bulletin, v. 120, p. 1,362,377. (Also available at http://dx.doi.org/10.1130/B26222.1 .) Tex., Baylor University Press, 145 p. woody and endemic plants, in Amos, B.B., and Gehlbach, studies in central Texas: Waco, Tex., Baylor University Press, p. 25. Anderson, Tamara, 2002, Conservation assessment for the Dakota and Wyoming: Custer, S. Dak., U.S. Department 34 p., accessed August 29, 2013, at http://www.fs.usda.gov/ Internet/FSE_DOCUMENTS/fsm9_012057.pdf . Anderson, Tamara, 2005, Oreohelix strigosa cooperi (Coo 2013, at http://www.fs.fed.us/r2/projects/scp/assessments/ coopersrockymountainsnail.pdf . available at http://www.twdb.state.tx.us/publications/ reports/numbered_reports/doc/R345/R345Complete.pdf . ) Backlund, Doug, 2009, The American dipper, Cinclus mexica nus and Parks, accessed September 29, 2012, at http://gfp. sd.gov/wildlife/management/diversity/black-hills-americandipper.aspx . work of the Edwards-Trinity aquifer system, west-central Texas: U.S. Geological Survey Professional Paper 1421–B, 61 p. (Also available at http://pubs.er.usgs.gov/publication/ pp1421B .) trend: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 50, p. 45. (Also available at http://dx.doi.org/10.1016/ S0031-0182(85)80005-5 .) ography, and evolution of the southeastern central Texas Eurycea clade Blepsimolge (Plethodontidae): Arlington, Tex., The University of Texas at Arlington, unpublished M.S. thesis, 127 p. climate of the last 10 million years: Quaternary Science http:// dx.doi.org/10.1016/0277-3791(91)90033-Q .) Bertelsen, M., Windhager, S., and Simmons, M., 2010, Protection Lands, Austin, Texas: accessed May 14, 2014, at f tp://ftp.ci.austin.tx.us/wildland/Water_Quality_Protec tion_Lands/Recommended%20Land%20Management_ Final.pdf .

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60 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota Supplement 1. Data Tables for Species Vulnerability Assessment This supplemental section contains links to data tables (in Microsoft Excel format) used for species vulnerability assess ment. Supplemental table S1 lists species of conservation concern that depend strongly on karst hydrology in the Balcones Escarpment and Black Hills regions, their conservation status, restriction to the assessment area (“endemic”), and if their climate change vulnerability was scored for this report. Supplemental table S1 lists Climate Change Vulnerability Index (CCVI) factor scores, information supporting those scores, and the CCVI results. Table S1. Species of conservation concern that depend strongly on karst hydrology in the Balcones Escarpment and Black Hills regions, their conservation status and restriction to the assessment area (“endemic”) , and whether their vulnerability to climate change was scored for this report . ( http://pubs.usgs.gov/sir/2014/5089/downloads/Table_S1-1.xlsx ) Table S1. Climate Change Vulnerability Index (CCVI) factor scores, information supporting those scores, and the CCVI results for select karst-hydrology-dependent species in the Balcones Escarpment and Black Hills regions . ( http://pubs.usgs.gov/sir/2014/5089/downloads/Table_S1-2.xlsx ) Supplement 2. Paleoclimate Inventory Supplemental table S2 (in Microsoft Excel format) is an inventory of paleoclimate studies that are of global, regional, and local relevance. Table S2. Review and inventory of local and regional paleoclimatic studies with relevance for the study areas . ( http://pubs.usgs.gov/sir/2014/5089/downloads/Table_S2-1.xlsx ) Supplement 3. Weather Research and Forecasting Model Namelist Files and Bias Adjustments http://pubs.usgs.gov/ sir/2014/5089/downloads/namelist.wps http:// pubs.usgs.gov/sir/2014/5089/downloads/namelist.input ) computation and data-output time steps, sets physics options, and sets other parameters such as those related to boundary condi http://pubs.usgs.gov/sir/2014/5089/downloads/namelist. README http://www.mmm.ucar.edu ]. daily mean, minimum, and maximum air temperatures were bias corrected so that the annual means of air temperatures (mean, minimum, and maximum) for the period 1981 matched those observed at the given weather station. Bias correction of air temperature was computed on the basis of annual means rather than monthly means to avoid unrealistic steps in air temperature time series at the end and beginning of each month. Annual air temperature and monthly precipitation bias adjustments are listed in table S3.

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Supplement 3. Weather Research and Forecasting Model Namelist Files and Bias Adjustments þ 61 Table S3. þ Bias corrections applied to the W eather Research and Forecasting Model output interpolated to the locations of weather stations for modeled sites. Name of modeled site Primary weather station Precipitation bias adjustment (millimeters per day) Air temperature bias adjustment (degrees Celsius) January February March April May June July August September October November December Maximum Mean Minimum Madison aquifer sites Spring IDW of nine weather stationsa-3.64 -3.24 -2.24 -1.34 -2.94 -7.20 -8.51 -5.23 -2.37 0.00 -1.62 -2.01 -0.81 -and CCVI site Lead -1.20 -0.71 1.01 1.91 -0.35 -7.24 -8.47 -6.50 -1.87 2.97 0.21 -0.17 4.10 3.98 2.81 CCVI site Custer -0.95 -0.01 0.06 0.51 -1.82 -7.76 -7.46 -4.18 -1.81 0.34 -0.30 -0.28 1.98 1.32 -0.74 Edwards aquifer sites Bexar County Index Well Hondo -4.30 -1.59 0.27 -1.55 0.55 2.94 1.82 1.26 -3.50 1.29 -2.07 -3.71 -2.00 -Barton Springs Dripping Springs 6E -1.30 -1.39 0.53 -2.63 1.16 4.09 2.03 1.14 -4.78 1.86 0.00 1.10 -1.90 -Comal Spring 1.67 2.04 3.13 0.32 3.20 7.75 10.31 6.57 -4.66 4.36 3.57 2.40 -1.39 -CCVI site Boerne -1.98 0.04 0.88 -1.79 1.44 4.06 2.92 2.33 -2.64 2.96 0.90 0.21 0.96 0.88 -0.76aLocation is the approximate centroid of the contributing watershed. Publishing support provided by: þ Rolla and Denver Publishing Service Centers For more information concerning this publication, contact: þ Director, USGS South Dakota Water Science Center þ 1608 Mountain V iew Road þ Rapid City , South Dakota 57702 þ (605) 394 Or visit the South Dakota Water Science Center Web site at: þ enhttp://sd.water.usgs.gov/

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62 Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota

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Back cover photographs . Upper left, Springflow at Comal Springs, Texas. Photograph by Michael Nyman, U.S. Geological Survey. Upper right, Upstream view of the U.S. Geological Survey streamgage at Rhoads Fork Spring near Rochford, South Dakota. Photograph by John Stamm, U.S. Geological Survey.

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ISSN 2328-0328 (online) http://dx.doi.org/10.3133/sir201 45089 Stamm and others — Climate and Hydrologic Response of Karst Aquifers, and Species Vulnerability, Texas and South Dakota — SIR 2014


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