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USGS2009

A Chronosequence Feasibility Assessment of Emergency Fire Rehabilitation Records within the Intermountain Western United States - Final Report to the Joint Fire Science Program - Project 08-S-08

Department of the Interior (DOI) bureaus have invested heavily (for example, the U.S. Bureau of Land Management (BLM) spent more than $60 million in fiscal year 2007) in seeding vegetation for emergency stabilization and burned area rehabilitation of non-forested arid lands over the past 10 years. The primary objectives of these seedings commonly are to (1) reduce the post-fire dominance of non-native annual grasses, such as cheatgrass (Bromus tectorum) and red brome (Bromus rubens); (2) minimize the probability of recurrent fire; and (3) ultimately produce desirable vegetation characteristics (for example, ability to recover following disturbance [resilience], resistance to invasive species, and a capacity to support a diverse flora and fauna). Although these projects historically have been monitored to varying extents, land managers currently lack scientific evidence to verify whether seeding arid and semiarid lands achieves desired objectives. Given the amount of resources dedicated to post-fire seeding projects, a synthesis of information determining the factors that result in successful treatments is critically needed. Although results of recently established experiments and monitoring projects eventually will provide useful insights for the future direction of emergency stabilization and burned area rehabilitation programs, a chronosequence approach evaluating emergency stabilization and burned area rehabilitation treatments (both referenced hereafter as ESR treatments) over the past 30 years could provide a comprehensive assessment of treatment success across a range of regional environmental gradients. By randomly selecting a statistically robust sample from the population of historic ESR treatments in the Intermountain West, this chronosequence approach would have inference for most ecological sites in this region. The goal of this feasibility study was to compile and examine historic ESR records from BLM field offices across the Intermountain West to determine whether sufficient documentation existed for a future field-based chronosequence project. We collected ESR records and data at nine BLM field offices in four States (Oregon, Idaho, Nevada, and Utah) and examined the utility of these data for the development of a chronosequence study of post-fire seeding treatments from multiple sites and different ages (since seeding) throughout the Intermountain West. We collected records from 730 post-fire seeding projects with 1,238 individual seeding treatments. Records from each project ranged from minimal reporting of the project's occurrence to detailed documentation of planning, implementation, and monitoring. Of these 1,238 projects, we identified 468 (38 percent) that could potentially be used to implement a field-based chronosequence study. There were 206 ground-seeding treatments and 262 aerial-seeding treatments within this initial population, not including hand plantings. We also located a considerable number of additional records from other potential field offices that would be available for the chronosequence study but have yet to be compiled for this feasibility report. There are a number of potential challenges involved in going forward with a field-based chronosequence study derived from data collected at these nine BLM offices. One challenge is that not all seed mixtures in ESR project files have on-the-ground confirmation about what was sown or rates of application. Most projects, particularly records before 2000, just list the planned or purchased seed mixtures. Although this could potentially bias assessments of factors influencing establishment rates of individual species for treatments conducted before 2000, a chronosequence study would not be intended to assess success solely at the species-level. Treatment success would be evaluated based on the establishment of healthy vegetation communities, such as the abundance and density of perennial species, regardless of their lifeforms (grasses, fo

Open-File Report↗

USGS2009

Controlling the spread of invasive species while sampling

Invasive species have a substantial impact on natural resource management. The economic cost of invasive species to people in the United States is an estimated US$137 billion annually (Pimental et al. 2000). The environmental cost is much greater and usually incalculable (Pimental et al. 2005). Nearly half of the plant and animal species federally listed in the United States' Endangered Species Act are threatened or endangered primarily as a consequence of invasive species that directly prey on native species or outcompete them for limited resources (Wilcove et al. 1998; Pimental et al. 2005) The result is reduced population numbers and, sometimes, local extinction of native plants and animals (Pimental at al. 2005). Such environmental damage is often irreparable. As natural resource managers, it is our responsibility to manage and conserve valuable natural resources. However, if our focus is limited to specific projects and tasks at hand, we may overlook the broader ramifications of our actions and unintentionally contribute to the invasive species problem. This chapter focuses on measures that should be taken to present, minimize, or control the spread of invasive species in the routine work we do as natural resource professionals. Inadvertently transporting potentially harmful organisms undermines our purposed as natural resource professionals. It is imperative that we understand that pathways that we create and strive to eliminate (when possible) or minimize the potential damage that may result from our actions. A combination of technologies, education, codes of conduct, and government overshot, as recommended by the Ecological Society of America, can prevent invasive species introductions from pathways that already exist (Lodge et al. 2006). In the long run, a purposeful prevention strategy for stopping unintentional species introductions will promote responsible natural resource management and will help us to achieve agency goals.

Book chapter↗

USGS2017

Evaluation and use of U.S. Environmental Protection Agency Clean Watersheds Needs Survey data to quantify nutrient loads to surface water, 1978–2012

Changes in municipal and industrial point-source discharges over time have been an important factor affecting nutrient trends in many of the Nation’s streams and rivers. This report documents how three U.S. Environmental Protection Agency (EPA) national datasets—the Permit Compliance System, the Integrated Compliance Information System, and the Clean Watersheds Needs Survey—were evaluated for use in the U.S. Geological Survey National Water-Quality Assessment project to assess the causes of nutrient trends. This report also describes how a database of total nitrogen load and total phosphorous load was generated for select wastewater treatment facilities in the United States based on information reported in the EPA Clean Watersheds Needs Survey. Nutrient loads were calculated for the years 1978, 1980, 1982, 1984, 1986, 1988, 1990, 1992, 1996, 2000, 2004, 2008, and 2012 based on average nitrogen and phosphorous concentrations for reported treatment levels and on annual reported flow values. The EPA Permit Compliance System (PCS) and Integrated Compliance Information System (ICIS), which monitor point-source facility discharges, together are the Nation’s most spatially comprehensive dataset for nutrients released to surface waters. However, datasets for many individual facilities are incomplete, the PCS/ICIS historical data date back only to 1989, and historical data are available for only a limited number of facilities. Additionally, inconsistencies in facility reporting make it difficult to track or identify changes in nutrient discharges over time. Previous efforts made by the U.S. Geological Survey to “fill in” gaps in the PCS/ICIS data were based on statistical methods—missing data were filled in through the use of a statistical model based on the Standard Industrial Classification code, size, and flow class of the facility and on seasonal nutrient discharges of similar facilities. This approach was used to estimate point-source loads for a single point in time; it was not evaluated for use in generating a consistent data series over time. Another national EPA dataset that is available is the Clean Watersheds Needs Survey (CWNS), conducted every 4 years beginning 1973. The CWNS is an assessment of the capital needs of wastewater facilities to meet the water-quality goals set in the Clean Water Act. Data collected about these facilities include location and contact information for the facilities; population served; flow and treatment level of the facility; estimated capital needs to upgrade, repair, or improve facilities for water quality; and nonpoint-source best management practices. Total nitrogen and total phosphorous load calculations for each of the CWNS years were based on treatment level information and average annual outflow (in million gallons per day) from each of the facilities that had reported it. Treatment levels categories (such as Primary, Secondary, or Advanced) were substituted with average total nitrogen and total phosphorous concentrations for each treatment level based on those reported in literature. The CWNS dataset, like the PCS/ICIS dataset, has years where facilities did not report either a treatment level or an annual average outflow, or both. To fill in the data gaps, simple linear assumptions were made based on each facility’s responses to the survey in years bracketing the data gap or immediately before or after the data gap if open ended. Treatment level and flow data unique to each facility were used to complete the CWNS dataset for that facility.

Scientific Investigations Report↗

USGS2013

Invasive species in southern Nevada

Southern Nevada contains a wide range of topographies, elevations, and climactic zones emblematic of its position at the ecotone between the Mojave Desert, Great Basin, and Colorado Plateau ecoregions. These varied environmental conditions support a high degree of biological diversity (Chapter 1), but they also provide opportunities for a wide range of invasive species. In addition, the population center of the Las Vegas valley, and the agricultural area scattered throughout Clark, Lincoln, and Nye counties, all connected by a network of roads and highways, plus ephemeral and perennial watercourses, provide abundant opportunities for new invaders to be transported into and within southern Nevada (Brooks 2009; Brookes and Lair 2009). Invasive species are a concern for land managers because they can compete directly with native species (Brooks 2000; Chambers and others 2007; DeFlaco and others 2003, 2007; Mazzola and others 2010), change habitat conditions (Brooks and Esque 2002; Esque and others 2010; Miller and others 2011), and alter ecosystems properties (Brooks and Matchett 2006; Brooks and Pyke 2001; Evans and others 2001). Many invasive species have already established and spread to the point that they are now considered to pose significant problems in southern Nevada. However, there are likely many more than have wither not been transported to or colonized the region, or have established by for various reasons not spread or increased in abundance to the point where they have a significant impact. Land managers must understand both current and potential future problems posed by invasive species to appropriately prioritize management actions. This chapter addressed Sub-goal 1.2 in the SNAP Science Research Strategy (table 1.3; Turner and others 2009), which is to protect southern Nevada's ecosystems from the adverse impacts of invasive species. It provides a brief overview of the key concepts associated with the ecology and management of invasive species, and includes information relevant to all five strategic goals identified by the National Invasive Species Council: prevention, early detection and rapid response, control and management, restoration, and organization collaboration (National Invasive Species Council 2001, 2008). Restoration also is discussed in a broader context in Chapter 5 and 7. This chapter does not present a comprehensive review of all invasive species associated land management issues in southern Nevada, but rather uses key species of concern to illustrate invasion ecology concepts and management strategies. It is focused on terrestrial and aquatic plants and animals, and does not address potential invasive taxa from the other Kingdoms. The information presented herein is intended to provide a foundation upon which land management plans can be developed and project-level decisions can be made relative to the management of invasive species in southern Nevada.

Nevada↗

USGS2016

Shifting currents: Progress, setbacks, and shifts in policy and practice

The Wisconsin Academy’s initial Waters of Wisconsin project (WOW I) facilitated a statewide conversation between 2000 and 2003 around one main question: How can we ensure healthy aquatic ecosystems and clean, abundant water supplies for tomorrow’s Wisconsin? Robust participation in this conversation underscored the important role citizens have in the stewardship of our waters, and we found enthusiastic support for farsighted policies—based on sound science—to manage our water legacy. Overall, we found that Wisconsinites cherish water and see our waters as essential to our way of life in Wisconsin. Nationally, our state ranks 25th in land area but has the fourth-highest area covered by water. Wisconsin is 20th in population but is second only to Florida in the number of fishing licenses sold each year. Clean water supports billions of dollars’ worth of economic activity through tourism, agriculture, and industry. From the Northwoods cabin to the Port of Milwaukee to the Wisconsin Dells, water shapes our state’s identity. Our tradition of safeguarding Wisconsin’s waters is grounded in values such as responsibility to family and future generations, respect for land and wildlife, protecting public health and safety, and caring for water as a common good, as articulated in the state’s Public Trust Doctrine (see page 9). These deeply held values have also shaped a conservation ethic, and its legacy has served many generations who depend upon and enjoy the waters of the state. Through WOW I, we identified the need to overcome the institutional and disciplinary separation of science, policy, and management protocols through a more integrated approach to water management. WOW also affirmed that the Wisconsin Department of Natural Resources (DNR) and other public agencies play a critical role in sound scientific application, citizen participation, and the practical implementation of policy while balancing public and private interests toward the goal of a clean water future. More than a decade has passed since our first statewide WOW conversation and the report that captured recommendations from its participants: Waters of Wisconsin: The Future of Our Aquatic Ecosystems and Resources. Drawing from a diverse and growing set of stakeholders from across the state, the Wisconsin Academy initiated a new conversation in 2012 (known as WOW II) to assess progress in regard to our 2003 recommendations. We also sought to review the status of waters in Wisconsin today. The result of this renewed conversation is Shifting Currents: Progress, Setbacks, and Shifts in Policy and Practice. The new report assesses progress in brief, and explores in greater depth the continuing and emerging challenges to water quality, supply, and aquatic ecosystems in Wisconsin. In this report, we first review the context and frameworks for public decision-making about water and then examine some of the root causes—or “drivers”—and ecological stressors that underlie many of the symptoms we see in the form of pollution or ecosystem degradation in Wisconsin. This is followed by a summary of current water issues, many of which had been identified in the 2003 report and remain relevant today. We examine progress since 2003 but also setbacks, and discuss issues that we are likely to continue to face in the coming decades, including controlling agricultural runoff, mitigating climate change and grappling with its effects on the state’s waters, protecting groundwater from bacterial contamination and other pollutants, and preventing groundwater depletion. We also attempt to anticipate issues on the horizon. We offer a deeper look at some particular challenges, such as phosphorus pollution and groundwater contamination. We then consider the current decision-making framework and how it is shaping our capacity to respond to water challenges in Wisconsin. Finally, we offer recommendations and identify opportunities to safeguard Wisconsin’s waters in the decades ahead. From its inception, the Wisconsin Academy’s Waters of Wisconsin Initiative has brought together a diverse community of experts from across the state and from varied fields and areas of interest, to address challenges and seize opportunities related to our precious waters. We have done so as a matter of both principle and practical reality: the state of our waters reflects the ways we interact not only with them, but also with one another and our institutions. The WOW Initiative has aimed to provide guidance for Wisconsin citizens in sustaining the health of our aquatic ecosystems and the resilience of our water supplies over the long term.

Report↗

USGS2003

Sedimentation rates in the marshes of Sand Lake National Wildlife Refuge

Impoundments located within river systems in the Northern Great Plains are vulnerable to sediment inputs because intensive agriculture in watersheds has increased soil erosion and sediments in rivers. At the request of the U.S. Fish and Wildlife Service (FWS), we evaluated the vertical accretion of sediment in the Mud Lake impoundment of Sand Lake National Wildlife Refuge (NWR), Brown County, South Dakota. The Mud Lake impoundment was created in 1936 by constructing a low-head dam across the James River. We collected sediment cores from the Mud Lake impoundment during August 2000 for determination of vertical accretion rates. Accretion rates were estimated using cesium-13 7 and lead-210 isotopic dating techniques to estimate sediment accretion over the past 100 years. Accretion rates were greatest near the dam (1.3 cm yr-1) with less accretion (0.2 cm yr-1) occurring in the upper reaches of Mud Lake. As expected, accretion was highest near the dam where water velocities and greater water depth facilitates sediment deposition. Higher rates of sedimentation (accretion> 2.0 cm year-1) occurred during the 1990s when river flows were especially high. Since 1959, sediment accretion has reduced maximum pool depth of Mud Lake near the dam by 55 cm. Assuming that sediment accretion rates remain the same in the future, we project Mud Lake will have a maximum pool depth of 77 and 51 cm by 2020 and 2040, respectively. Over this same time frame, water depths in the upper reaches of Mud Lake would be reduced to< 2 cm. Projected future loss of water depth will severely limit the ability of managers to manipulate pool levels in Mud Lake to cycle vegetation and create interspersion of cover and water to meet current wildlife habitat management objectives. As predicted for major dams constructed on rivers throughout the world, Mud Lake will have a finite life span. Our data suggests that the functional life span of Mud Lake since construction will be < 100 years. We anticipate that over the next 20 years, sediments entering Mud Lake will reduce water depths to the point that current wildlife management objectives cannot be achieved through customary water-level manipulations. Sedimentation impacts are not unique to the Sand Lake NWR. It is widely accepted that impoundments trap sediments and shallow impoundments, such as those managed by the FWS, are especially vulnerable. Given the ecological impacts associated with loss of water depths, we recommend that managers begin evaluating the long-term wildlife management goals for the refuge relative to associated costs and feasibility of options available to enhance and maximize the life span of existing impoundments, including upper watershed management.

Report↗

USGS2005

Naturally Occurring Arsenic in Ground Water, Norman, Oklahoma, 2004, and Remediation Options for Produced Water

In 2000, the U.S. Environmental Protection Agency (EPA) reviewed the arsenic drinking water standard for public water supplies. Considering the available research and statistics on the health effects of arsenic ingestion, the EPA reduced the Maximum Contaminant Level (MCL) for public drinking water from 50 micrograms per liter (?g/L) to 10 ?g/L (U.S. Environmental Protection Agency, 2001a). As a result of the more stringent standard, the EPA estimates that about 3,000 public water providers across the United States must take action to meet the new standard before it becomes effective on January 23, 2006 (U.S. Environmental Protection Agency, 2001b). The City of Norman (City) is one of several Oklahoma municipalities affected by the new arsenic standard. About 20 percent of Norman?s water is supplied by wells completed in the Central Oklahoma (Garber-Wellington) aquifer; the rest is supplied by Lake Thunderbird (fig. 1) or purchased from Oklahoma City. The Norman well field is composed of 24 active wells, and water produced from about half of the wells will not be in compliance with the new MCL (figs. 2 and 3). Chemical treatment of water with elevated arsenic is possible, but it is generally cost prohibitive. Another costly solution is simply to abandon the high-arsenic wells and replace them with new wells in low-arsenic areas. In the next phase of well construction beginning in 2005, the City plans to construct as many as 30 new wells in northeast Norman (Bryan Mitchell, City of Norman, oral commun., 2005). The new wells will replace production lost to the new arsenic standard and add new production to keep pace with rapidly growing consumer demand. Well modification to exclude arsenic-bearing water from existing wells is a more cost-effective solution, but it requires a great deal of knowledge about local aquifer properties and individual well dynamics to decide which wells are good candidates for modification. With the goal of determining if well modification can be used to bring some of Norman?s high-arsenic wells into compliance with the new arsenic standard, the EPA Office of Research and Development (ORD) initiated a three-year research project in 2003 with participation from the U.S. Geological Survey (USGS), Oklahoma State University, and the City of Norman. The primary objectives of the project are to: (1) determine where naturally occurring arsenic is entering wells by collecting water samples at different depths, (2) investigate the utility of new methods for collecting water-quality data in a pumping well, (3) better understand the stratigraphy and composition of aquifer rocks, (4) assess 10 wells for the possibility of arsenic remediation by well modification, and (5) evaluate the effectiveness of well modification in bringing marginal wells into compliance with the new arsenic MCL. The purpose of this report is to describe the occurrence of arsenic in ground water near Norman, Oklahoma, and available options for reducing arsenic concentrations in produced ground water.

Fact Sheet↗

USGS2014

Spatially explicit habitat models for 28 fishes from the Upper Mississippi River System (AHAG 2.0)

Environmental management actions in the Upper Mississippi River System (UMRS) typically require pre-project assessments of predicted benefits under a range of project scenarios. The U.S. Army Corps of Engineers (USACE) now requires certified and peer-reviewed models to conduct these assessments. Previously, habitat benefits were estimated for fish communities in the UMRS using the Aquatic Habitat Appraisal Guide (AHAG v.1.0; AHAG from hereon). This spreadsheet-based model used a habitat suitability index (HSI) approach that drew heavily upon Habitat Evaluation Procedures (HEP; U.S. Fish and Wildlife Service, 1980) by the U.S. Fish and Wildlife Service (USFWS). The HSI approach requires developing species response curves for different environmental variables that seek to broadly represent habitat. The AHAG model uses species-specific response curves assembled from literature values, data from other ecosystems, or best professional judgment. A recent scientific review of the AHAG indicated that the model’s effectiveness is reduced by its dated approach to large river ecosystems, uncertainty regarding its data inputs and rationale for habitat-species response relationships, and lack of field validation (Abt Associates Inc., 2011). The reviewers made two major recommendations: (1) incorporate empirical data from the UMRS into defining the empirical response curves, and (2) conduct post-project biological evaluations to test pre-project benefits estimated by AHAG. Our objective was to address the first recommendation and generate updated response curves for AHAG using data from the Upper Mississippi River Restoration-Environmental Management Program (UMRR-EMP) Long Term Resource Monitoring Program (LTRMP) element. Fish community data have been collected by LTRMP (Gutreuter and others, 1995; Ratcliff and others, in press) for 20 years from 6 study reaches representing 1,930 kilometers of river and >140 species of fish. We modeled a subset of these data (28 different species; occurrences at sampling sites as observed in day electrofishing samples) using multiple logistic regression with presence/absence responses. Each species’ probability of occurrence, at each sample site, was modeled as a function of 17 environmental variables observed at each sample site by LTRMP standardized protocols. The modeling methods used (1) a forward-selection process to identify the most important predictors and their relative contributions to predictions; (2) partial methods on the predictor set to control variance inflation; and (3) diagnostics for LTRMP design elements that may influence model fits. Models were fit for 28 species, representing 3 habitat guilds (Lentic, Lotic, and Generalist). We intended to develop “systemic models” using data from all six LTRMP study reaches simultaneously; however, this proved impossible. Thus, we “regionalized” the models, creating two models for each species: “Upper Reach” models, using data from Pools 4, 8, and 13; and “Lower Reach” models, using data from Pool 26, the Open River Reach of the Mississippi River, and the La Grange reach of the Illinois River. A total of 56 models were attempted. For any given site-scale prediction, each model used data from the three LTRMP study reaches comprising the regional model to make predictions. For example, a site-scale prediction in Pool 8 was made using data from Pools 4, 8, and 13. This is the fundamental nature and trade-off of regionalizing these models for broad management application. Model fits were deemed “certifiably good” using the Hosmer and Lemeshow Goodness-of-Fit statistic (Hosmer and Lemeshow, 2000). This test post-partitions model predictions into 10 groups and conducts inferential tests on correspondences between observed and expected probability of occurrence across all partitions, under Chi-square distributional assumptions. This permits an inferential test of how well the models fit and a tool for reporting when they did not (and perhaps why). Our goal was to develop regionalized models, and to assess and describe circumstances when a good fit was not possible. Seven fish species composed the Lentic guild. Good fits were achieved for six Upper Reach models. In the Lower Reach, no model produced good fits for the Lentic guild. This was due to (1) lentic species being much less prominent in the Lower Reach study areas, and (2) those that do express greater prominence principally do so only in the La Grange reach of the Illinois River. Thus, developing Lower Reach models for Lentic species will require parsing La Grange from the other two Lower Reach study areas and fitting separate models. We did not do that as part of this study, but it could be done at a later time. Nine species comprised the Lotic guild. Good fits were achieved for seven Upper Reach models and six Lower Reach models. Four species had good fits for both regions (flathead catfish, blue sucker, sauger, and shorthead redhorse). Three species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (blue catfish, rock bass, and skipjack herring). Twelve species comprised the Generalist guild. Good fits were achieved for five Upper Reach models and eight Lower Reach models. Six species had good fits for both regions (brook silverside, emerald shiner, freshwater drum, logperch, longnose gar, and white bass). Two species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (red shiner and blackstripe topminnow). Poorly fit models were almost always due to the diagnostic variable “field station,” a surrogate for river mile. In these circumstances, the residuals for “field station” were non-randomly distributed and often strongly ordered. This indicates either fitting “pool scale” models for these species and regions, or explicitly model covariances between “field station” and the other predictors within the existing modeling framework. Further efforts on these models should seek to resolve these issues using one of these two approaches. In total, nine species, representing two of the three guilds (Lotic and Generalist), produced well-fit models for both regions. These nine species should comprise the basis for AHAG 2.0. Additional work, likely requiring downscaling of the regional models to pool-scale models, will be needed to incorporate additional species. Alternately, a regionalized AHAG could be comprised of those species, per region, that achieved well-fit models. The number of species and the composition of the regional species pools will differ among regions as a consequence. Each of these alternatives has both pros and cons, and managers are encouraged to consider them fully before further advancing this approach to modeling multi-species habitat suitability.

Upper Mississippi River System↗

USGS2011

Overview of the ARkStorm scenario

The U.S. Geological Survey, Multi Hazards Demonstration Project (MHDP) uses hazards science to improve resiliency of communities to natural disasters including earthquakes, tsunamis, wildfires, landslides, floods and coastal erosion. The project engages emergency planners, businesses, universities, government agencies, and others in preparing for major natural disasters. The project also helps to set research goals and provides decision-making information for loss reduction and improved resiliency. The first public product of the MHDP was the ShakeOut Earthquake Scenario published in May 2008. This detailed depiction of a hypothetical magnitude 7.8 earthquake on the San Andreas Fault in southern California served as the centerpiece of the largest earthquake drill in United States history, involving over 5,000 emergency responders and the participation of over 5.5 million citizens. This document summarizes the next major public project for MHDP, a winter storm scenario called ARkStorm (for Atmospheric River 1,000). Experts have designed a large, scientifically realistic meteorological event followed by an examination of the secondary hazards (for example, landslides and flooding), physical damages to the built environment, and social and economic consequences. The hypothetical storm depicted here would strike the U.S. West Coast and be similar to the intense California winter storms of 1861 and 1862 that left the central valley of California impassible. The storm is estimated to produce precipitation that in many places exceeds levels only experienced on average once every 500 to 1,000 years. Extensive flooding results. In many cases flooding overwhelms the state’s flood-protection system, which is typically designed to resist 100- to 200-year runoffs. The Central Valley experiences hypothetical flooding 300 miles long and 20 or more miles wide. Serious flooding also occurs in Orange County, Los Angeles County, San Diego, the San Francisco Bay area, and other coastal communities. Windspeeds in some places reach 125 miles per hour, hurricane-force winds. Across wider areas of the state, winds reach 60 miles per hour. Hundreds of landslides damage roads, highways, and homes. Property damage exceeds $ 300 billion, most from flooding. Demand surge (an increase in labor rates and other repair costs after major natural disasters) could increase property losses by 20 percent. Agricultural losses and other costs to repair lifelines, dewater (drain) flooded islands, and repair damage from landslides, brings the total direct property loss to nearly $ 400 billion, of which $ 20 to $ 30 billion would be recoverable through public and commercial insurance. Power, water, sewer, and other lifelines experience damage that takes weeks or months to restore. Flooding evacuation could involve 1.5 million residents in the inland region and delta counties. Business interruption costs reach $ 325 billion in addition to the $ 400 billion property repair costs, meaning that an ARkStorm could cost on the order of $ 725 billion, which is nearly 3 times the loss deemed to be realistic by the ShakeOut authors for a severe southern California earthquake, an event with roughly the same annual occurrence probability. The ARkStorm has several public policy implications: (1) An ARkStorm raises serious questions about the ability of existing federal, state, and local disaster planning to handle a disaster of this magnitude. (2) A core policy issue raised is whether to pay now to mitigate, or pay a lot more later for recovery. (3) Innovative financing solutions are likely to be needed to avoid fiscal crisis and adequately fund response and recovery costs from a similar, real, disaster. (4) Responders and government managers at all levels could be encouraged to conduct risk assessments, and devise the full spectrum of exercises, to exercise ability of their plans to address a similar event. (5) ARkStorm can be a reference point for application of Federal Emergency Management Agency (FEMA) and California Emergency Management Agency guidance connecting federal, state and local natural hazards mapping and mitigation planning under the National Flood Insurance Plan and Disaster Mitigation Act of 2000. (6) Common messages to educate the public about the risk of such an extreme disaster as the ARkStorm scenario could be developed and consistently communicated to facilitate policy formulation and transformation. These impacts were estimated by a team of 117 scientists, engineers, public-policy experts, insurance experts, and employees of the affected lifelines. In many aspects the ARkStorm produced new science, such as the model of coastal inundation. The products of the ARkStorm are intended for use by emergency planners, utility operators, policymakers, and others to inform preparedness plans and to enhance resiliency.

California↗

USGS2015

Southern Salish Sea Habitat Map Series: Admiralty Inlet

In 2010 the Environmental Protection Agency, Region 10 initiated the Puget Sound Scientific Studies and Technical Investigations Assistance Program, designed to support research in support of implementing the Puget Sound Action Agenda. The Action Agenda was created in response to Puget Sound having been designated as one of 28 estuaries of national significance under section 320 of the U.S. Clean Water Act, and its overall goal is to restore the Puget Sound Estuary's environment by 2020. The Southern Salish Sea Mapping Project was funded by the Assistance Program request for proposals process, which also supports a large number of coastal-zone- and ocean-management issues. The issues include the recommendations of the Marine Protected Areas Work Group to the Washington State Legislature (Van Cleve and others, 2009), which endorses a Puget Sound and coast-wide marine conservation needs assessment, gap analysis of existing Marine Protected Areas (MPA) and recommendations for action. This publication is the first of four U.S. Geological Survey Scientific Investigation Maps that make up the Southern Salish Sea Mapping Project. The remaining three map blocks to be published in the future, located south of Admiralty Inlet, are shown in figure 1. Puget Sound is a deep, fjord-type estuary covering an area of 2,330 km 2 in the Pacific Northwest region of the United States (fig. 1). It is connected to the ocean by the Strait of Juan de Fuca, a turbulent passage approximately 160 km in length and 22 km wide at its west end, expanding to over 40 km wide at its east end (Thomson, 1994). During the Pleistocene, the area was occupied several times by lobes of continental ice, resulting in a complex basin-fill of glacial and interglacial deposits that are locally as thick as 1100 m (Johnson and others, 2001). The last glaciation, called the Fraser glaciation, began after 28,800±740 14 C yr B.P. when ice started a slow expansion (Clague, 1981). At peak advance the westward Juan de Fuca lobe reached the edge of the continental shelf through the Juan de Fuca Strait shortly before 14,460±200 14 C yr B.P. (Herzer and Bornhold, 1982). The southward Puget lobe advanced to its terminal position in Puget Sound by around 14,150 14 C yr B.P. (Porter and Swanson, 1998). Ice retreated from its maximum to northern Whidbey Island by 13,650±350 14 C yr B.P. (Dethier and others, 1995). Retreating glaciers resulted in a thick sequence of ice-contact, glacial-marine sediment, and early post-glacial sediments (Linden and Schurrer, 1988). These deposits have experienced the effects of a marine transgression followed by regression, resulting in a sea-level several tens of meters lower than the present day (Linden and Schurrer, 1988). A second transgression brought sea level to about the present level by around 5,470±120 14 C yr B.P. (Clague and others, 1982) establishing the present oceanographic and geologic environment Puget Sound is separated into four interconnected basins; Whidbey, Central (Main), Hood Canal, and South (Thomson, 1994). The Whidbey, Central, and Hood Canal basins are the three main branches of the Puget Sound estuary and are separated from the Strait of Juan de Fuca by a double sill at Admiralty Inlet. The Admiralty Inlet map area includes the Inlet and a portion of the Whidbey Basin (fig. 1). The shallower South Basin is separated by a sill at Tacoma Narrows and is highly branched with numerous finger inlets. Flow within Puget Sound is dominated by tidal currents of as much as 1 m/s at Admiralty Inlet, reducing to approximately 0.5 m/s in the Central Basin (Lavelle and others, 1988). The lack of silt and clay-sized sediments in the Admiralty Inlet map area is likely a result of the strong currents (see Ground-Truth Studies for the Admiralty Inlet Map Area, sheet 3). The subtidal component of flow reaches approximately 0.1 m/s and is driven by density gradients arising from the contrast in salty ocean water at the entrance and freshwater inputs from stream flow (Lavelle and others, 1988). The total freshwater input to Puget Sound is approximately 3.4 x 10 6 m 3 /day, primarily from the Skagit River (Cannon, 1983). The subtidal circulation mostly consists of a two-layered flow in the basins with fresher water exiting at the surface and saltier water entering at depth (Ebbesmeyer and Cannon, 2001). In general, surface waters flow north and deeper waters flow south; variations arise from wind effects that can drive a surface current in the same direction as the wind, and a baroclinic response in the lower layer to about 100-m depth (Matsuura and Cannon, 1997). Oceanographic properties are influenced by temporal forcing parameters such as reduced stream flow during the 2000-01 drought that increased surface salinity and decreased differences between surface and bottom waters (Newton and others, 2003). On offshore seismic-reflection profiles, Pleistocene strata (excluding latest Pleistocene glacial and post-glacial deposits) form a distinct seismic unit, bounded below by pre-Tertiary or Tertiary basement and above by typically flat-lying latest Pleistocene to Holocene deposits that fill in erosional or depositional relief (Johnson and others, 2001). Cores from central Puget Sound have accumulation rates that range from 85 to 1200 mg/cm 2 /yr, or 0.12 to 2.4 cm/yr; the highest accumulation rates are near the southern end of central Puget Sound (Carpenter and others, 1985). Carpenter and others (1985) un-weighted arithmetic mean of accumulation rates for central Puget Sound deeper stations is 480±340 (± one standard deviation) mg/cm 2 /yr. Lavelle and others (1985) also found rates as high as 1200 mg/cm 2 /yr over the past approximately 70 years in cores in the Central Basin off of and north and south of Elliott Bay. Puget Sound basin rates are comparable to rates in midshelf silt deposits on the Washington coast north of the Columbia River (Nittrouer and others, 1979). The deep subtidal (in other words, below SCUBA depths) habitats of Puget Sound are relatively poorly known. A few subtidal surveys exist for several habitat types from the 1960s and 1970s (reviewed in Dethier, 1990), using grab and box core data. The Dethier (1990) review divides habitat up into Coast and Marine Ecological Classification Standard (CMECS) substrate, water column energy, and depth zones but does not attempt to map these habitats, rather it is an inventory of habitats found in the area and the flora and fauna associated with each habitat. The approach of the Southern Salish Sea Mapping project is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, and bottom-sediment sampling data. This approach is based in part on methods presented and data collection and product needs identified at the Washington State Seafloor Mapping Workshop (Washington State Seafloor Mapping Workshop Steering Committee, 2008), attended by coastal and marine managers and scientists. The map products display seafloor geomorphology and substrate, and identify potential marine benthic habitats. It is emphasized that the more interpretive habitat and geology maps rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. Oceanographic current and wave data is not included in this analysis, however, the accompanying geographic information system (GIS) data set is designed and intended to be combined with oceanographic and biologic data sets assembled by others in the future and some of the GIS data has already been incorporated in the unpublished Nature Conservancy Benthic Habitats of Puget Sound database. This publication includes four map sheets, explanatory text, and a descriptive pamphlet. Each map sheet is published as a portable document format (PDF) file. ESRI ArcGIS compatible geotiffs (for example, bathymetry) and shapefiles (for example video observation points) will be available for download in the data catalog associated with this publication (Cochrane, 2015). An ArcGIS Project File with the symbology used to generate the map sheets is also provided. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html .

Washington↗

USGS2009

Movement and habitat use of sika and white-tailed deer on Assateague Island National Seashore, Maryland

This research project was conducted to describe habitat use of sika deer ( Cervus nippon ) and white-tailed deer ( Odocoileus virginianus ) and possibly attribute the effects of ungulate herbivory to specific deer species, if spatial separation in habitat use could be identified. Sturm (2007) conducted an exclosure study to document the effect of feral horse ( Equus caballus ) herbivory, deer herbivory, and horse and deer herbivory combined on plant communities. Sturm (2007) found that ungulate herbivory reduced plant species richness, evenness, and diversity in the maritime forest and affected species composition in all habitats studied. Sturm (2007) also found that herbivory on some species could be directly attributable to either horse or deer. However, the effects of sika and white-tailed deer herbivory could not be separated via an exclosure study design because of the difficulty of passively excluding one deer species but not the other. We captured white-tailed deer and sika deer in January–March of 2006 and 2007 throughout the Maryland portion of Assateague Island. Deer were fitted with radio-collars and their survival and locations monitored via ground telemetry. Up to four locations were acquired per deer each week during early (May–June) and late (August–September) growth periods for vegetation on the island. Also, we estimated deer locations during a dormant vegetation period (November– December 2006). We used these data to estimate survival and harvest rates, document movements, and model habitat use. We captured and fitted 50 deer with radio-collars over the course of the study. Of these 50 deer, 36 were sika and 14 were white-tailed deer. Of the 36 sika deer, 10 were harvested, three were likely killed by hunters but not recovered, and one died of natural causes while giving birth. Of the 14 white-tailed deer, three were harvested, one was illegally killed, and two were censored because of study-related mortality. Annual survival was 0.48 (95% CI = 0.16–0.82) for male white-tailed deer, 0.74 (95% CI = 0.44–0.91) for female white-tailed deer, 0.56 (95% CI = 0.35–0.75) for male sika deer, and 0.86 (95% CI = 0.70–0.94) for female sika deer. The harvest rate was 0.12 (95% CI = 0.04–0.27) for female sika deer, 0.44 (95% CI = 0.25–0.65) for male sika deer, 0.18 (95% CI = 0.05–0.51) for female white-tailed deer, and 0.38 (95% CI = 0.10–0.78) for male white-tailed deer. Annual survival rates for both species were similar to what has been observed in other populations. Unfortunately, small sample sizes for male white-tailed deer limited inferences about harvest and survival rates, but harvest rates of females for both species were similar to other published studies. Hunting was the primary cause of mortality, and outside the hunting season survival was 0.98–1.00 for all species and sexes. We found that the home range area of sika deer was much greater than the home range area of white-tailed deer, but failed to detect any difference between sexes or among seasons. Sika deer also made long-distance movements and left the Maryland portion of Assateague Island. No sika deer left Assateague island during our study, but we did document the dispersal of a male whitetailed deer to the mainland. In their native range, sika deer have been able to readily expand populations and occupy vacant habitat (Kaji et al. 2000; Kaji et al. 2004). The long distance movements we observed on Assateague Island, especially relative to white-tailed deer, may reflect the ability of this species to exploit food resources that may be limited in quality or quantity, or both. However, we did not collect data to assess use of food resources by sika deer and whether this may have influenced long distance movements. We found both species of deer were less likely to use a habitat the further it was located from cover, which was defined as tall shrub or forest vegetation. For every 10 m (32 ft) from cover each species of deer was 1.23–1.38 times less likely to use any given habitat. Patterns in use of vegetation classes were similar across species and seasons. Relative to forest habitat, both species avoided dune herbaceous, disturbed lands, sand, and water categories. Both species neither avoided nor preferred developed herbaceous, low shrub, marsh herbaceous, and tall shrub categories compared to the forest category. However, there were consistent differences between the two species. During spring, white-tailed deer were more likely than sika deer to use forested, tall shrub, disturbed herbaceous, and sand areas, but were less likely to use all other habitats. During summer, habitat use was similar between the two species except that white-tailed deer tended to use forested habitat more. During winter, white-tailed deer were less likely to use dune herbaceous, low shrub, and forested habitats than sika deer. Sturm (2007) identified differential browsing on plant species between horses and deer, but his experimental design did not permit detection of differential browsing between sika and whitetailed deer. Our study of habitat use did not provide information to identify plant species that may be differentially consumed by sika and white-tailed deer based on differences in habitat use. We envision two approaches to addressing the effects of deer browsing. One approach would be further research that identifies the food habits of both deer species at the plant species level. This would be similar to food habits research conducted by Keiper (1985) and others or could involve direct observation of food consumption by both species. However, both fecal analysis and direct observation would be time-consuming and not guaranteed to identify differences. If the goal of ungulate population management is to protect the island ecosystem, another approach involving manipulation of deer abundance and monitoring the response of plant species known to be preferentially consumed by deer would be a more direct method of assessing effects of deer herbivory (Sturm 2007). Moreover, such an approach is not predicated on detecting differences between deer species. Direct manipulation of deer abundance could be incorporated into an adaptive management program (Williams et al. 2007) and may provide greater benefits to the management of ASIS in the long term. Harvest management decisions for white-tailed deer and sika deer are made on an ongoing basis and by coupling these decisions with a vegetative monitoring program it may be possible to reduce or minimize adverse effects of ungulate herbivory. Furthermore, management of feral horses could be incorporated into the decision process.

Maryland, Virginia↗