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Alan L. Flint

Publications and source records attributed to Alan L. Flint.

At least 19 recordsLinked to original sources

Climate and land change impacts on future managed wetland habitat: A case study from California’s Central Valley

Concept California’s Central Valley provides critical habitat for migratory waterbirds, yet only 10% of naturally occurring wetlands remain. Competition for limited water supplies and climate change will impact the long-term viability of these intensively managed habitats. Objectives Forecast the distribution, abundance, and connectivity of surface water and managed wetland habitats, using 5 spatially explicit (270 m 2 ) climate/land use/water prioritization scenarios. Mapping potential future dynamic flooded habitat used by waterbirds and other wetland-dependent wildlife to inform management decisions. Methods We integrated a climate-driven hydrologic water use model with a spatially explicit land change model, to examine stakeholder-driven scenarios of future land change, climate, and water use and their impacts on future habitat availability. Results Declining water availability is the dominant driver of habitat loss across scenarios. The hot/dry scenarios showed the greatest declines in January flooded area by 2101—an important month for overwintering waterbirds. In contrast, higher water supplies in wet climates drive perennial cropland conversion and loss of potential habitat. Potential flooded cropland declined (25 and 33%) under warmer/wetter climate conditions due to this conversion to perennial crops, exposing habitat vulnerability. Conclusion Climate-driven loss of water availability had a greater impact on flooded habitat availability than land-use change. When combined, climate change and the conversion of potentially flooded cropland to perennial cropland will threaten future waterbird habitat particularly in January, the peak of the migratory bird season, even when habitat restoration goals are met. Stakeholder-informed scenario analysis can identify target areas for potential habitat change, vulnerability, and conservation.

California

Selecting the optimal fine-scale historical climate data for assessing current and future hydrological conditions

High-resolution historical climate grids are readily available and frequently used as inputs for a wide range of regional management and risk assessments, including water supply, ecological processes, and as baseline for climate change impact studies that compare them to future projected conditions. Because historical gridded climates are produced using various methods, their portrayal of landscape conditions differ, which becomes a source of uncertainty when they are applied to subsequent analyses. Here we tested the range of values from five gridded climate datasets. We compared their values to observations from 1231 weather stations, first using each dataset’s native scale, and then after each was rescaled to 270-m resolution. We inputted the downscaled grids to a mechanistic hydrology model and assessed the spatial results of six hydrological variables across California, in 10 ecoregions and 11 large watersheds in the Sierra Nevada. PRISM was most accurate for precipitation, ClimateNA for maximum temperature, and TopoWx for minimum temperature. The single most accurate dataset overall was PRISM due to the best performance for precipitation and low air temperature errors. Hydrological differences ranged up to 70% of the average monthly streamflow with an average of 35% disagreement for all months derived from different historical climate maps. Large differences in minimum air temperature data produced differences in modeled actual evapotranspiration, snowpack, and streamflow. Areas with the highest variability in climate data, including the Sierra Nevada and Klamath Mountains ecoregions, also had the largest spread for snow water equivalent, recharge, and runoff.

Journal of Hydrometeorology

A basin-scale approach to estimating recharge in the desert: Anza-Cahuilla groundwater basin, CA

The Anza-Cahuilla groundwater basin located mainly in the semi-arid headwaters of the Santa Margarita River watershed in southern California is the principle source of groundwater for a rural disadvantaged community and two Native American Tribes, the Ramona Band of Cahuilla and the Cahuilla. Groundwater in the study area is derived entirely from precipitation and managing groundwater sustainably requires an accurate assessment of the water balance components, yet long-term estimates do not exist. Demand for groundwater in the region has increased and groundwater quality has decreased due to population growth and increased irrigated cropland. To characterize monthly long-term natural recharge and runoff estimates, a physically-based water balance model (Basin Characterization Model) was locally calibrated and validated using nearby streamgages and published estimates of climatic and hydrologic variables. The average modeled annual recharge and runoff from 1981 to 2010 was 5.4 × 10 6 and 1.2 × 10 7 m 3 , respectively, for the study area. Recharge and runoff do not reliably occur in large amounts every year and recharge rarely occurs in the groundwater basin footprint. These long-term estimates can be used by water managers, stakeholders, and Native American Tribes to develop plans for sustainable management of future water resources, and as inputs to a three-dimensional groundwater model.

California

The basin characterization model—A regional water balance software package

This report documents the computer software package, Basin Characterization Model, version 8 (BCMv8)—a monthly, gridded, regional water-balance model—and provides detailed operational instructions and example applications. After several years of many applications and uses of a previous version, CA-BCM, published in 2014, the BCMv8 was refined to improve the accuracy of the water-balance components, particularly the recharge estimate, which is the most difficult to accurately assess. The improvement of the various water-balance components targeted the actual evapotranspiration component, which, in turn, reduced the uncertainty of the recharge estimate. The improvement of this component was enabled by the availability of a national, gridded actual-evapotranspiration product from the U.S. Geological Survey that was unique in its scope to combine remotely sensed spatial variability and ground-based long-term water-balance constraints. This dataset provided the ability to assess monthly actual evapotranspiration for 62 vegetation types and to perform regional calibration in watersheds throughout California with the objective of closing the water balance using improved estimates for each component. The refinements, including vegetation-specific evapotranspiration, enabled the development of applications that could explore various aspects of landscape disturbance, such as wildfire, forest management, or urbanization. The improvements to BCMv8 also provided the ability to assess long-term sustainability of water resources under a variety of management applications or future climate projections.

California

Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and northern Chihuahua, Mexico

Changes in population, agricultural development and practices (including shifts to more water-intensive crops), and climate variability are increasing demands on available water resources, particularly groundwater, in one of the most productive agricultural regions in the Southwest—the Rincon and Mesilla Valley parts of Rio Grande Valley, Doña Ana and Sierra Counties, New Mexico, and El Paso County, Texas. The goal of this study was to produce an integrated hydrological simulation model to help evaluate water-management strategies, including conjunctive use of surface water and groundwater for historical conditions, and to support long-term planning for the Rio Grande Project. This report describes model construction and applications by the U.S. Geological Survey, working in cooperation and collaboration with the Bureau of Reclamation. This model, the Rio Grande Transboundary Integrated Hydrologic Model, simulates the most important natural and human components of the hydrologic system, including selected components related to variations in climate, thereby providing a reliable assessment of surface-water and groundwater conditions and processes that can inform water users and help improve planning for future conditions and sustained operations of the Rio Grande Project (RGP) by the Bureau of Reclamation. Model development included a revision of the conceptual model of the flow system, construction of a Transboundary Rio Grande Watershed Model (TRGWM) water-balance model using the Basin Characterization Model, and construction of an integrated hydrologic flow model with MODFLOW-One-Water Hydrologic Flow Model version 2 (referred to as MF-OWHM2). The hydrologic models were developed for and calibrated to historical conditions of water and land use, and parameters were adjusted so that simulated values closely matched available measurements (calibration). The calibrated model was then used to assess the use and movement of water in the Rincon Valley, Mesilla Basin, and northern part of the Conejos-Médanos Basin, with the entire region referred to as the “Transboundary Rio Grande” or TRG. These tools provide a means to understand hydrologic system response to the evolution of water use in the region, its availability, and potential operational constraints of the RGP. The conceptual model identified surface-water and groundwater inflows and outflows that included the movement and use of water both in natural and in anthropogenic systems. The groundwater-flow system is characterized by a layered geologic sedimentary sequence combined with the effects of groundwater pumping, operation of the RGP, natural runoff and recharge, and the application of irrigation water at the land surface that is captured and reused in an extensive network of canals and drains as part of the conjunctive use of water in the region. Historical groundwater-level fluctuations followed a cyclic pattern that were aligned with climate cycles, which collectively resulted in alternating periods of wet or dry years. Periods of drought that persisted for one or more years are associated with low surface-water availability that resulted in higher rates of groundwater-level decline. Rates of groundwater-level decline also increased during periods of agricultural intensification, which necessitated increasing use of groundwater as a source of irrigation water. Agriculture in the area was initially dominated by alfalfa and cotton, but since 1970 more water-intensive pecan orchards and vegetable production have become more common. Groundwater levels substantially declined in subregions where drier climate combined with increased demand, resulting in periods of reduced streamflows. Most of the groundwater was recharged in the Rio Grande Valley floor, and most of the pumpage and aquifer storage depletion was in Mesilla Basin agricultural subregions. A cyclic imbalance between inflows and outflows resulted in the modeled cyclic depletion (groundwater withdrawals in excess of natural recharge) of the groundwater basin during the 75-year simulation period of 1940–2014. Changes in groundwater storage can vary considerably from year to year, depending on land use, pumpage, and climate conditions. Climatic drivers of wet and dry years can greatly affect all inflows, outflows, and water use. Although streamflow and, to a minor extent, precipitation during inter-decadal wet-year periods replenished the groundwater historically, contemporary water use and storage depletion could have reduced the effects of these major recharge events. The average net groundwater flow-rate deficit for 1953–2014 was estimated to be about 1,090 acre-feet per year.

Chihuahua, New Mexico, Texas

PFHydro: A new watershed-scale model for post-fire runoff simulation

Runoff increases after wildfires that burn vegetation and create a condition of soil-water repellence (SWR). A new post-fire watershed hydrological model, PFHydro, was created to explicitly simulate vegetation interception and SWR effects for four burn severity categories: high, medium, low severity and unburned. The model was applied to simulate post-fire runoff from the Upper Cache Creek Watershed in California, USA. Nash–Sutcliffe modeling efficiency (NSE) was used to assess model performance. The NSE was 0.80 and 0.88 for pre-fire water years (WY) 2000 and 2015, respectively. NSE was 0.88 and 0.93 for WYs 2016 (first year post-fire) and 2017 respectively. The simulated percentage of surface runoff in total runoff of WY 2016 was about six times that of pre-fire WY 2000 and three times that of WY 2015. The modeling results suggest that SWR is an important factor for post-fire runoff generation. The model was successful at simulating SWR behavior.

California

Hydrologic resilience from summertime fog and recharge: A case study for coho salmon recovery planning

Fog and low cloud cover (FLCC) and late summer recharge increase stream baseflow and decrease stream temperature during arid Mediterranean climate summers, which benefits salmon especially under climate warming conditions. The potential to discharge cool water to streams during the late summer (hydrologic capacity; HC) furnished by FLCC and recharge were mapped for the 299 subwatersheds ranked Core, Phase 1, or Phase 2 under the National Marine Fisheries Service Recovery Plan that prioritized restoration and threat abatement action for endangered Central California Coast Coho Salmon evolutionarily significant unit. Two spatially continuous gridded datasets were merged to compare HC: average hrs/day FLCC, a new dataset derived from a decade of hourly National Weather Satellite data, and annual average mm recharge from the USGS Basin Characterization Model. Two use‐case scenarios provide examples of incorporating FLCC‐driven HC indices into long‐term recovery planning. The first, a thermal analysis under future climate, projected 65% of the watershed area for 8–19 coho population units as thermally inhospitable under two global climate models and identified several units with high resilience (high HC under the range of projected warming conditions). The second use case investigated HC by subwatershed rank and coho population, and identified three population units with high HC in areas ranked Phase 1 and 2 and low HC in Core. Recovery planning for cold‐water fish species would benefit by including FLCC in vulnerability analyses.

California

Characterizing the influence of fire on hydrology in southern California

The chaparral-dominated national forests of southern California were in part established to provide water provision services to the surrounding urban populations and irrigation for agriculture. However, water provision in the form of groundwater recharge and surface runoff depends on the climatological conditions of any given year and also landscape-scale disturbances such as fire. Fire is increasing in frequency in southern California and understanding its impacts both immediately postfire and as vegetation recovers, and the interactions between fire and hydrology, are key components to managing federal lands effectively. In this study we focus on nine fires in a study area that encompasses the four southern California national forests (Los Padres, Angeles, San Bernardino, and Cleveland) and use a water balance model to investigate the effects of water provision services post-fire at a regional scale. We found that runoff and recharge increased post-fire, with increases in recharge being greater with recovery times ranging from 2 to 4 y post-fire. Vegetation recovery occurred 2 y post-fire for all basins as indicated by remotely sensed imagery measuring vegetation greenness having returned to or exceeded pre-fire values for the basin. We found that runoff and recharge were more sensitive to the effects of climate than to length of time post-fire. Findings from these modeling tools allow users to anticipate the impact of fire on water provision services in the region and develop management strategies that help reduce the impacts of wildfire.

California

Characterization of hydrology and sediment transport following drought and wildfire in Cache Creek, California

The worst drought in California in over 1,200 years occurred between 2012-2017 (Griffin, 2014), depleting surface water and groundwater supply and drying out the soils past wilting point. In the summer of 2015, the Jerusalem and Rocky fires burned roughly 40,000 acres within the Cache Creek watershed. To fully characterize the post-fire effects in the Cache Creek watershed, an hourly model of streamflow and sediment transport was developed using the Hydrological Simulation Program – FORTRAN (HSPF). This model requires air temperature, precipitation, and potential evapotranspiration as climate inputs. Hourly station data are sparse in the area and may not capture the variability of elevation and local climatology patterns within the watershed. A technique used previously to spatially-interpolate daily-climate station data has improved the characterization of local and regional climate patterns on a daily scale in areas with sparse data (Flint et al., 2014). This technique was extended to hourly observed data to produce spatially-varying climate inputs for the Cache Creek hydrologic model to run as a continuous multi-year simulation with hourly time steps. Monthly PRISM grids were used in a two-step scaling method with climate Gradient and Inverse Distance Squared (GIDS) maps (Nalder and Wein, 1998) to develop daily grids, then the daily grids were used to scale hourly climate GIDS maps. This method captures the temporal variability at each climate station yet preserves the regional monthly spatial structure of the PRISM data. Hydrologic calibration used data from water year 2015, and validation used the same parameters for water year 2016. The model was run through water year 2017 to characterize the effects of wildfire on hydrology and sediment transport. For final simulations, the model was run at an hourly time step from June 2014 through September 2017 to ensure a model initiation period of 4 months prior to the target simulation period used for analysis. Sediment parameters were initially set using the existing Sacramento River Basin model for this sub-watershed area and then iteratively adjusted in the calibration process. To simulate a fire across the landscape, sediment parameters for water years 2016-17 were further modified for burned sub-basins to represent post-fire vegetation and soils in 2016, then partial recovery in 2017. Results were inconclusive for drought and wildfire effects on runoff. Modeled peak flows generally underpredicted observed peak flows; however, the modeled storm volumes were only slightly under or over the observed storm volumes. Sediment transport was sensitive to the watershed disturbances and R^2 values for daily mean suspended concentrations (SSC) and sediment discharge were 0.70 and 0.75, respectively. Simulated hourly values correlated less strongly with observed instantaneous SSC and sediment discharge (R^2 values of 0.56 and 0.46, respectively).

California

Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California

In situ soil moisture datasets are important inputs used to calibrate and validate watershed, regional, or statewide modeled and satellite-based soil moisture estimates. The soil moisture dataset presented in this report includes hourly time series of the following: soil temperature, volumetric water content, water potential, and total soil water content. Data were collected by the U.S. Geological Survey at five locations in California: three sites in the central Sierra Nevada and two sites in the northern Coast Ranges. This report provides a description of each of the study areas, procedures and equipment used, processing steps, and time series data from each site in the form of comma-separated values (.csv) tables.

California

High‐elevation evapotranspiration estimates during drought: Using streamflow and NASA Airborne Snow Observatory SWE observations to vlose the upper Tuolumne River Basin eater balance

Hydrologic variables such as evapotranspiration (ET) and soil water storage are difficult to observe across spatial scales in complex terrain. Streamflow and lidar‐derived snow observations provide information about distributed hydrologic processes such as snowmelt, infiltration, and storage. We use a distributed streamflow data set across eight basins in the upper Tuolumne River region of Yosemite National Park in the Sierra Nevada mountain range, and the NASA Airborne Snow Observatory (ASO) lidar‐derived snow data set over 3 years (2013–2015) during a prolonged drought in California, to estimate basin‐scale water balance components. We compare snowmelt and cumulative precipitation over periods from the ASO flight to the end of the water year against cumulative streamflow observations. The basin water balance residual term (snow melt plus precipitation minus streamflow) is calculated for each basin and year. Using soil moisture observations and hydrologic model simulations, we show that the residual term represents short‐term changes in basin water storage over the snowmelt season, but that over the period from peak snow water equivalent (SWE) to the end of summer, it represents cumulative basin‐mean ET. Warm‐season ET estimated from this approach is 168 (85–252 at 95% confidence), 162 (0–326) and 191 (48–334) mm averaged across the basins in 2013, 2014, and 2015, respectively. These values are lower than previous full‐year and point ET estimates in the Sierra Nevada, potentially reflecting reduced ET during drought, the effects of spatial variability, and the part‐year time period. Using streamflow and ASO snow observations, we quantify spatially‐distributed hydrologic processes otherwise difficult to observe.

California

Characterizing drought in California: new drought indices and scenario-testing in support of resource management

Introduction California’s recent drought (2012–2016) has implications throughout the state for natural resource management and adaptation planning and has generated many discussions about drought characterization and recovery. This study characterizes drought conditions with two indices describing deficits in natural water supply and increases in landscape stress developed on the basis of water balance modeling, at a fine spatial scale to assess the variation in conditions across the entire state, and provides an in-depth evaluation for the Russian River basin in northern California to address local resource management by developing extreme drought scenarios for consideration in planning and adaptation. Methods We employed the USGS Basin Characterization Model to characterize drought on the basis of water supply (a measure of recharge plus runoff) and landscape stress (climatic water deficit). These were applied to the state and to the Russian River basin where antecedent soil moisture conditions were evaluated and extreme drought scenarios were developed and run through a water management and reservoir operations model to further explore impacts on water management. Results Drought indices indicated that as of the end of water year 2016 when reservoirs were full, additional water supply and landscape replenishment of up to three average years of precipitation in some locations was needed to return to normal conditions. Antecedent soil conditions in the Russian River were determined to contribute to very different water supply results for different years and were necessary to understand to anticipate proper watershed response to climate. Extreme drought scenarios manifested very different kinds of drought and recovery and characterization helps to guide the management response to drought. Conclusions These scenarios and indices illustrate how droughts differ with regard to water supply and landscape stress and how long warm droughts recover much more slowly than short very dry droughts due to the depletion of water in the soil and unsaturated zone that require filling before runoff can occur. Recognition of ongoing conditions and likelihood of recovery provides tools and information for a range of resource managers to cope with drought conditions.

California

Increasing soil organic carbon to mitigate greenhouse gases and increase climate resiliency for California

Rising air temperatures are projected to continue to drive up urban, agricultural, and rangeland water use, straining both surface and groundwater resources. Scientific studies have shown that managing farms, ranches, and public lands to increase soil carbon can increase soil waterholding capacity and increase hydrologic benefits such as increased baseflows and aquifer recharge, reduced flooding and erosion, and reduced climate-related water deficits. Coincident improvements in forage and crop yields are also indicated, while simultaneously sequestering carbon, reducing atmospheric greenhouse gases and mitigating climate change. This study was developed to consider the multiple benefits of increasing the organic matter content of soils across California’s working lands. Study results indicate that a one-time ¼” application of compost to rangelands can lead to carbon sequestration rates in soils that are maximized after approximately 15 years, and more than offset greenhouse gas emissions stimulated by the compost addition for at least five decades longer. Modeled increases in total soil organic matter of 3% enhanced hydrologic benefits across 97% of working lands, and reduced climate change impacts. Economic valuation indicated all benefits increasing over time, demonstrating a large potential for the California carbon market to support incentives in regionalizing the impacts in the coming decades. Socioeconomic and related land use pressures pose barriers to implementing management practices to increase soil organic matter by driving conversion of rangeland to urban or to more greenhouse-gas emission intensive agriculture. Results can be effectively used with land use change scenarios to identify where on California’s working lands hydrologic benefits of soil organic matter enhancement coincide with development risk, highlighting counties in California in which there may be resilience to climate change when strategic soil management and land conservation are combined.

California

Climate change refugia and habitat connectivity promote species persistence

Background Climate change refugia, areas buffered from climate change relative to their surroundings, are of increasing interest as natural resource managers seek to prioritize climate adaptation actions. However, evidence that refugia buffer the effects of anthropogenic climate change is largely missing. Methods Focusing on the climate-sensitive Belding’s ground squirrel ( Urocitellus beldingi ), we predicted that highly connected Sierra Nevada meadows that had warmed less or shown less precipitation change over the last century would have greater population persistence, as measured by short-term occupancy, fewer extirpations over the twentieth century, and long-term persistence measured through genetic diversity. Results Across California, U. beldingi were more likely to persist over the last century in meadows with high connectivity that were defined as refugial based on a suite of temperature and precipitation factors. In Yosemite National Park, highly connected refugial meadows were more likely to be occupied by U. beldingi . More broadly, populations inhabiting Sierra Nevada meadows with colder mean winter temperatures had higher values of allelic richness at microsatellite loci, consistent with higher population persistence in temperature-buffered sites. Furthermore, both allelic richness and gene flow were higher in meadows that had higher landscape connectivity, indicating the importance of metapopulation processes. Conversely, anthropogenic refugia, sites where populations appeared to persist due to food or water supplementation, had lower connectivity, genetic diversity, and gene flow, and thus might act as ecological traps. This study provides evidence that validates the climate change refugia concept in a contemporary context and illustrates how to integrate field observations and genetic analyses to test the effectiveness of climate change refugia and connectivity. Conclusions Climate change refugia will be important for conserving populations as well as genetic diversity and evolutionary potential. Our study shows that in-depth modeling paired with rigorous fieldwork can identify functioning climate change refugia for conservation.

California

Erosion of refugia in the Sierra Nevada meadows network with climate change

Climate refugia management has been proposed as a climate adaptation strategy in the face of global change. Key to this strategy is identification of these areas as well as an understanding of how they are connected on the landscape. Focusing on meadows of the Sierra Nevada in California, we examined multiple factors affecting connectivity using circuit theory, and determined how patches have been and are expected to be affected by climate change. Connectivity surfaces varied depending upon the underlying hypothesis, although meadow area and elevation were important features for higher connectivity. Climate refugia that would promote population persistence were identified from downscaled climate layers, based on locations with minimal climatic change from historical conditions. This approach was agnostic to specific species, yielding a broad perspective about changes and localized habitats. Connectivity was not a consistent predictor of refugial status in the 20th century, but expected future climate refugia tended to have higher connectivity than those that recently deviated from historical conditions. Climate change is projected to reduce the number of refugial meadows on a variety of climate axes, resulting in a sparser network of potential refugia across elevations. Our approach provides a straightforward method that can be used as a tool to prioritize places for climate adaptation.

California

Geothermal implications of a refined composition-age geologic map for the volcanic terrains of southeast Oregon, northeast California, and southwest Idaho, USA

Sufficient temperatures to generate steam likely exist under most of the dominantly volcanic terrains of southeast Oregon, northeast California, and southeast Idaho, USA, but finding sufficient permeability to allow efficient advective heat exchange is an outstanding challenge. A new thematic interpretation of existing state-level geologic maps provides an updated and refined distribution of the composition and age of geologic units for the purposes of assessing the implications for measurement and development of geothermal resources. This interpretation has been developed to better understand geothermal and hydrologic resources of the region. Comparison of the new geologic categories with available hydrologic data shows that younger volcanogenic terrains tend to have higher primary permeability than older terrains. Decrease in primary permeability with age is attributable to weathering and hydrothermal alteration of volcanogenic deposits to pore-filling clays and deposition of secondary deposits (e.g., zeolites). Spring density as a function of geology and precipitation can be used to infer groundwater flow path length within the upper aquifers. Beneath the upper aquifers, we postulate that, due to accelerated hydrothermal alteration at temperatures ~>30 °C, primary permeability at depths of geothermal interest will be limited, and that secondary permeability is a more viable target for hydrothermal fluid withdrawal. Because open fractures resulting from tensile stresses will affect all geologic layers, regions with a significant amount of groundwater flow through shallow, structurally controlled secondary permeability may overlay zones of deep secondary permeability. Regardless of whether the shallow permeability is connected with the deep permeability, shallow groundwater flow can mask the presence of deep hydrothermal flow, resulting in blind geothermal systems. Ideally, hydraulic connectivity between shallow and deep secondary permeability is limited, so that shallow groundwater does not cool potential geothermal reservoirs.

Conference Paper

Climate change influences on pollinator, forest, and farm interactions across a climate gradient

Climate impact models are often implemented at horizontal resolutions (“scales”) too coarse to be readily applied in local impact assessments. However, recent advancements in fine-scale modeling are allowing the creation of impact models that can be applied to landscape-scale adaptation planning. Here, we illustrate the use of fine-scale impact models for landscape-scale adaptation planning of pollination services for six sites in Central America. The strategies include the identification of (1) potential reservoir areas that may retain bee diversity and serve as a source of recolonization after climate shocks such as droughts; and (2) potential restoration areas, where improving forest cover is likely to lead to increases in pollinator services both in the present and in the future. Coarse-scale (>1-km horizontal resolution) climatic controls on pollinator diversity and forest cover determine the general location of these areas in our six landscapes. Fine-scale (<100-m horizontal resolution) variation in climatic water deficit provides an index of forest health which can help identify intervention strategies within these zones. All sites have significant areas in which protecting or restoring forest cover is likely to enhance pollination services. The gradient in rainfall change across the study sites dictates choice of adaptation strategies.

Climatic Change

Shrinking windows of opportunity for oak seedling establishment in southern California mountains

Seedling establishment is a critical step that may ultimately govern tree species’ distribution shifts under environmental change. Annual variation in the location of seed rain and microclimates results in transient “windows of opportunity” for tree seedling establishment across the landscape. These establishment windows vary at fine spatiotemporal scales that are not considered in most assessments of climate change impacts on tree species range dynamics and habitat displacement. We integrate field seedling establishment trials conducted in the southern Sierra Nevada and western Tehachapi Mountains of southern California with spatially downscaled grids of modeled water-year climatic water deficit (CWD wy ) and mean August maximum daily temperature ( T max ) to map historical and projected future microclimates suitable for establishment windows of opportunity for Quercus douglasii , a dominant tree species of warm, dry foothill woodlands, and Q. kelloggii , a dominant of cooler, more mesic montane woodlands and forests. Based on quasi-binomial regression models, Q. douglasii seedling establishment is significantly associated with modeled CWD wy and to a lesser degree with modeled T max . Q. kelloggii seedling establishment is most strongly associated with T max and best predicted by a two-factor model including CWD wy and T max . Establishment niche models are applied to explore recruitment window dynamics in the western Tehachapi Mountains, where these species are currently widespread canopy dominants. Establishment windows are projected to decrease by 50–95%, shrinking locally to higher elevations and north-facing slopes by the end of this century depending on the species and climate scenario. These decreases in establishment windows suggest the potential for longer-term regional population declines of the species. While many additional processes regulate seedling establishment and growth, this study highlights the need to account for topoclimatic controls and interannual climatic variation when assessing how seedling establishment and colonization processes could be affected by climate change.

California