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Climate change science and modeling

This chapter provides a brief background on climate change science, climate simulation models, and models that project the impacts of changes in climate on tree species and ecosystems. Throughout the chapter, boxes list resources for more information on each topic. A more detailed scientific review of climate change science, trends, and modeling can be found in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (IPCC 2014), and the Fourth National Climate Assessment (U.S. Global Climate Research Program [USGCRP] 2017).

Delaware, Maryland, New Jersey, New York, Pennsylv↗

Non-negligible near-term risk of extinction to the eastern migratory population of monarch butterflies—An updated assessment (2006–22)

The eastern migratory population of monarch butterflies ( Danaus plexippus ) started declining as early as the mid-1970s and seemed to stop declining by the early 2000s; the population now (about 2022) persists at a much-reduced abundance. Stochastic variation in abundance, at levels typical of monarch butterflies and other insects, was assessed to determine whether this population is at heightened risk of quasi-extinction, a level of abundance below which recovery of the migratory behavior is uncertain. Using previously published Bayesian state-space modeling methods it was determined roughly equivalent risk of quasi-extinction as was reported in 2016 for the species (28.7 percent [1.9–81.0 credible interval] and 52.0 percent [3.2–97.7 credible interval] at the 10- and 20-year marks, respectively). Though highly uncertain, the risk is non-negligibly positive. Warning signal analysis indicates the current dynamic is dominated by stochastic variation, which seems to be heightening risk with the passage of time. Increasing breeding opportunities through restoration of milkweed in its northern breeding locations seems to be the most promising means of mitigating extinction risk for this species.

Open-File Report↗

Estimated Ground-Water Withdrawals from the Death Valley Regional Flow System, Nevada and California, 1913-98

Ground-water withdrawals from 1913 through 1998 from the Death Valley regional flow system have been compiled to support a regional, three-dimensional, transient ground-water flow model. Withdrawal locations and depths of production intervals were estimated and associated errors were reported for 9,300 wells. Withdrawals were grouped into three categories: mining, public-supply, and commercial water use; domestic water use; and irrigation water use. In this report, groupings were based on the method used to estimate pumpage. Cumulative ground-water withdrawals from 1913 through 1998 totaled 3 million acre-feet, most of which was used to irrigate alfalfa. Annual withdrawal for irrigation ranged from 80 to almost 100 percent of the total pumpage. About 75,000 acre-feet was withdrawn for irrigation in 1998. Annual irrigation withdrawals generally were estimated as the product of irrigated acreage and application rate. About 320 fields totaling 11,000 acres were identified in six hydrographic areas. Annual application rates for high water-use crops ranged from 5 feet in Penoyer Valley to 9 feet in Pahrump Valley. The uncertainty in the estimates of ground-water withdrawals was attributed primarily to the uncertainty of application rate estimates. Annual ground-water withdrawal was estimated at about 90,000 acre-feet in 1998 with an assigned uncertainty bounded by 60,000 to 130,000 acre-feet.

Water-Resources Investigations Report↗

Use of environmental tracers to evaluate ground-water age and water-quality trends in a buried-valley aquifer, Dayton area, southwestern Ohio

Chlorofluorocarbons (CFC method) and tritium and helium isotopes (3H-3He method) were used as environmental tracers to estimate ground-water age in conjunction with efforts to develop a regional ground-water flow model of the buried-valley aquifer in the Dayton area, southwestern Ohio. This report describes results of CFC and water-quality sampling, summarizes relevant aspects of previously published work, and describes the use of 3H-3He ages to characterize temporal trends in ground-water quality of the buried-valley aquifer near Dayton, Ohio. Results of CFC sampling indicate that approximately 25 percent of the 137 sampled wells were contaminated with excess CFC's that rendered the ground water unsuitable for age dating. Evaluation of CFC ages obtained for the remaining samples indicated that the CFC compounds used for dating were being affected by microbial degradation. The degradation occurred under anoxic conditions that are found in most parts of the buried-valley aquifer. As a result, ground-water ages derived by the CFC method were too old and were inconsistent with measured tritium concentrations and independently derived 3H-3He ages. Limited data indicate that dissolved methane may play an important role in the degradation of the CFC's. In contrast, the 3H-3He technique was found to yield ground-water ages that were chemically and hydrologically reasonable. Ground-water ages derived by the 3H-3He technique were compared to values for selected water- quality characteristics to evaluate temporal trends in ground-water quality in the buried- valley aquifer. Distinct temporal trends were not identified for pH, alkalinity, or calcium and magnesium because of rapid equilibration of ground-water with calcite and dolomite in aquifer sediments. Temporal trends in which the amount of scatter and the number of outlier concentrations increased as ground-water age decreased were noted for sodium, potassium, boron, bromide, chloride, ammonia, nitrate, phosphate, sulfate, and organic carbon. Elevated concentrations of these constituents in shallow ground water are probably related to human activities. Temporal trends in which concentrations declined as ground-water age increased may reflect natural processes that reduce constituent concentrations to low levels. For example, the absence of nitrate detections in ground water recharged before 1980 may indicate natural removal of nitrate by bacterially mediated denitrification. Temporal trends observed for dissolved oxygen, iron, nitrate and silica indicate that these constituents may help identify recently (post-1990) recharged ground water.

Ohio↗

Analysis of trends in terrestrial vegetation at Mediterranean Coast Network Parks: Channel Islands National Park

The five islands comprising Channel Islands National Park (CHIS) experience natural gradients in temperature and moisture driven by ocean currents. Additionally, the islands were used as ranchlands and military land before becoming a national park, resulting in widespread erosion and vegetation change. As a result, CHIS spans gradients in climate as well as ranching duration and time since animal removal. Vegetation monitoring was initiated in 1984 on three islands (Anacapa, Santa Barbara, San Miguel), in 1990 on Santa Rosa Island, and in 1998 on Santa Cruz Island, with the goal of documenting the long-term response of island vegetation to ranch animal removal and climate fluctuations. Since that time, monitoring has documented the range of natural fluctuation in island environments over decades and provided insights into vegetation change in ecosystems unencumbered by ongoing development. Long-term vegetation monitoring at CHIS is therefore a rare example of an ecosystem experiment that demonstrates the results of management actions and serves as a baseline for land managers and scientists worldwide. Terrestrial vegetation data collected between 1984 and 2018 were modeled to estimate trends over time and to characterize relationships with covariates related to site characteristics, nonnative mammal removal programs, and water balance metrics. Data were analyzed for trends in vegetation cover, woody plant density, and plant community diversity grouped by life form and nativity across all islands and within individual islands, as well as for several individual species that dominate plant communities or present challenges to native plant recovery. In all, a total of 162 trend and covariate models were tested in this study, the details of which are provided in this report. Briefly, results reflect a decline in nonnative annual disturbance-thriving species with the reduction in animal grazing and trampling. Increasing trends were observed in native shrub density and native shrub recruitment density, as well as native shrub cover across all islands averaged together and on Santa Cruz Island. However, opposite trends were seen on the smaller islands of Santa Barbara and Anacapa, where increasing seabird activity may be damaging vegetation. Further results indicate the importance of soil moisture, relative humidity, fog, precipitation, site exposure, and solar radiation for vegetation patterns and trends. In many instances, there are apparent interacting effects of environmental variables with trends related to nonnative mammal removal and site location. Vegetation patterns in space and time emerge in the dataset as nuanced responses to interacting drivers.

Calfornia↗

GIS data for the Seaside, Oregon, Tsunami Pilot Study to modernize FEMA flood hazard maps

A Tsunami Pilot Study was conducted for the area surrounding the coastal town of Seaside, Oregon, as part of the Federal Emergency Management's (FEMA) Flood Insurance Rate Map Modernization Program (Tsunami Pilot Study Working Group, 2006). The Cascadia subduction zone extends from Cape Mendocino, California, to Vancouver Island, Canada. The Seaside area was chosen because it is typical of many coastal communities subject to tsunamis generated by far- and near-field (Cascadia) earthquakes. Two goals of the pilot study were to develop probabilistic 100-year and 500-year tsunami inundation maps using Probabilistic Tsunami Hazard Analysis (PTHA) and to provide recommendations for improving tsunami hazard assessment guidelines for FEMA and state and local agencies. The study was an interagency effort by the National Oceanic and Atmospheric Administration, U.S. Geological Survey, and FEMA, in collaboration with the University of Southern California, Middle East Technical University, Portland State University, Horning Geoscience, Northwest Hydraulics Consultants, and the Oregon Department of Geological and Mineral Industries. The pilot study model data and results are published separately as a geographic information systems (GIS) data report (Wong and others, 2006). The flood maps and GIS data are briefly described here.

Oregon↗

Future scenarios of land-use and land-cover change in the United States--the Marine West Coast Forests Ecoregion

Detecting, quantifying, and projecting historical and future changes in land use and land cover (LULC) has emerged as a core research area for the U.S. Geological Survey (USGS). Changes in LULC are important drivers of changes to biogeochemical cycles, the exchange of energy between the Earth’s surface and atmosphere, biodiversity, water quality, and climate change. To quantify the rates of recent historical LULC change, the USGS Land Cover Trends project recently completed a unique ecoregion-based assessment of late 20th century LULC change for the western United States. To characterize present LULC, the USGS and partners have created the National Land Cover Database (NLCD) for the years 1992, 2001, and 2006. Both Land Cover Trends and NLCD projects continue to evolve in an effort to better characterize historical and present LULC conditions and are the foundation of the data presented in this report. Projecting future changes in LULC requires an understanding of the rates and patterns of change, the major driving forces, and the socioeconomic and biophysical determinants and capacities of regions. The data presented in this report is the result of an effort by USGS scientists to downscale the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) to ecoregions of the conterminous United States as part of the USGS Biological Carbon Sequestration Assessment. The USGS biological carbon assessment was mandated by Section 712 of the Energy Independence and Security Act of 2007. As part of the legislative mandate, the USGS is required to publish a methodology describing, in detail, the approach to be used for the assessment. The development of future LULC scenarios is described in chapter 3.2 and appendix A. Spatial modeling is described in chapter 3.3.2 and appendix B and in Sohl and others (2011). In this report, we briefly summarize the major components and methods used to downscale IPCC-SRES scenarios to ecoregions of the conterminous United States, followed by a description of the Marine West Coast Forests Ecoregion, and lastly a description of the data being published as part of this report.

California;Oregon;Washington↗

Decision-support modeling and research priorities for establishing baseline conditions for outstandingly remarkable values, Obed Wild and Scenic River, Tennessee

The Obed River is the last undammed river in Tennessee. The Obed Wild and Scenic River is managed by the National Park Service and covers a protected area of the Obed River headwaters (including four contributing tributaries). The Obed Wild and Scenic River supports a unique ecosystem with eight federally listed species. The National Park Service is responsible for preserving the baseline free-flowing condition of the river and associated outstandingly remarkable values (ORVs). Previous studies have been mostly project-based with differing methods, thus complicating efforts to quantify long-term changes in environmental conditions. This report presents a science plan summarizing (1) ORV conditions, (2) recent results of a decision-support hydrologic model for OBRI, and (3) possible future research priorities. The decision-support model was created to model streamflow conditions and changes in the ORVs since park establishment in 1976 and during three additional time periods. Established baseline conditions could help with management of ORVs not dependent on streamflow.

Tennessee↗

Hydrogeology and steady-state simulation of ground-water flow in the San Juan Basin, New Mexico, Colorado, Arizona, and Utah

As part of a multidisciplinary regional aquifer-system analysis, a three-dimensional steady-state ground-water-flow model was constructed for the San Juan Basin in parts of New Mexico, Colorado, Arizona, and Utah. The model simulated ground- water flow in 12 hydrostratigraphic units representing all of the major sources of ground water from aquifers of Jurassic and younger age. Ten map reports in the U.S. Geological Survey Hydrologic Investigations Atlas 720 series were prepared in conjunction with this investigation. The units that were described in the atlases were the San Jose, Nacimiento, and Animas Formations; Ojo Alamo Sandstone; Kirtland Shale and Fruitland Formation; Pictured Cliffs Sandstone; Cliff House Sandstone; Menefee Formation; Point Lookout Sandstone; Gallup Sandstone; Dakota Sandstone; and Morrison Formation. Additional descriptions of the alluvial and landslide deposits, Chuska and Crevasse Canyon Sandstones, Lewis and Mancos Shales, Wanakah Formation, and Entrada Sandstone are included in this report. Much of the information in the HA-720 series was generated from digital computer data bases that were directly usable by the computer for compilation of input data for the model. In essence, the major components of the ground-water- flow model were described and documented in the series of hydrologic atlases. The primary finding resulting from the ground-water-flow simulation was that boundary conditions and internal geometry of the aquifers are the major controls of steady-state ground-water flow and hydraulic heads in the San Juan Basin. Another significant finding was that the computed steady-state ground- water flux is a very minor component (about 1 percent) of the total water budget of the basin.

Water-Resources Investigations Report↗

USGS Wildland Fire Workshop, EROS Data Center, Sioux Falls, SD, July 9-10, 1997

Report on the first workshop on USGS wildland fire expertise and capabilities. The workshop brought together operational and research representatives ofthe Federal fire management agencies to initiate a more comprehensive assessment ofthe USGS's capabilities and the appropriate role(s) for USGS interaction and involvement with the fire community. The report discusses how the USGS can play a significant role in wildland fire research and offer the fire community several unique capabilities. Foremost capability is the role as data producer; fire detection, assessment, ecological modeling, and rehabilitation and restoration relying on digital elevation models, digital line-graphs, national technical means, and image data are also discussed. The bureau offers technical expertise using geographic information systems (GIS), image processing and analysis, data base management and clearinghouse experience, and access to national technical means data. The bureau must exploit the USGS's expertise and prominence in wildland fire research. The USGS is an experienced player in fire ecology, fire assessment, and fuels loading research. Finally, the USGS also offers strong interdisciplinary experience in watershed and geologic landslide modeling, which is key for assessing postfire effects.

Report↗

Groundwater-flow model of the Treasure Valley, southwestern Idaho, 1986–2015

Most of the population of the Treasure Valley and the surrounding area of southwestern Idaho and easternmost Oregon depends on groundwater for domestic supply, either from domestic or municipal-supply wells. Current and projected rapid population growth in the area has caused concern about the long-term sustainability of the groundwater resource. In 2016, the U.S. Geological Survey, in cooperation with the Idaho Water Resource Board and the Idaho Department of Water Resources, began a project to construct a numerical groundwater-flow model of the westernmost portion of the western Snake River Plain aquifer system, called the Treasure Valley. The development of the model was guided by several objectives, including: to improve the understanding of groundwater and surface water interactions; to facilitate conjunctive water management; to provide a tool for water resources planning; and to provide a tool for water allocation. The model was constructed with a spatial scale and level of detail that aimed to meet these objectives while balancing the sometimes-competing goals of fast runtimes, numerical stability, usability, and parsimony. The Treasure Valley Groundwater Flow Model (TVGWFM) is a three-dimensional finite-difference numerical model constructed using MODFLOW 6 (Langevin and others, 2017, Documentation for the MODFLOW 6 Groundwater Flow Model: U.S. Geological Survey Techniques and Methods, book 6, chap. A55, 197 p., https://doi.org/10.3133/tm6A55 ). The model covers the westernmost portion of the western Snake River Plain and is discretized into a regular grid of 64 by 65 cells with a side length of 1 mile and 6 layers of varying depth and active area. A historical model period was developed consisting of 360 month-long stress periods for 1986–2015. The model builds upon previous modeling efforts by adding a transient period, incorporating new head and discharge observations to constrain parameters, incorporating information from the hydrogeologic framework model (HFM) of Bartolino (2019, Hydrogeologic framework of the Treasure Valley and surrounding area, Idaho and Oregon: U.S. Geological Survey Scientific Investigations Report 2019–5138, https://doi.org/10.3133/sir20195138 ) and incorporating refined estimates of evapotranspiration and irrigation classification of lands in the study area. The TVGWFM includes all significant components of recharge to and discharge from the aquifer. Inflows include canal seepage, irrigation and precipitation recharge, mountain-front recharge, rivers and stream seepage, and seepage from Lake Lowell. Outflows include discharge to agricultural drainage ditches, discharge to rivers and streams, pumping, and discharge to Lake Lowell. Each recharge or discharge component is represented separately using individual MODFLOW 6 packages. Parameter values were derived with a combination of trial-and-error steps and automated parameter estimation using PEST software (Doherty, J.E., 2005, PEST, model-independent parameter estimation–User manual: Watermark Numerical Computing, https://pesthomepage.org/documentation ). Parameter estimates were constrained with several types of observation data, including water levels, water level changes, vertical water level differences, drain discharges, change in drain discharges, river seepage, seepage from Lake Lowell, and change in seepage from Lake Lowell. Material properties from the hydrogeologic framework were also used to assign the minimum and maximum values of some parameters. A final parameter realization was reached that minimized residuals between the observed and modelled values for the various observation groups. Mean residuals for the observation groups were 15.4 feet (ft) for water levels, 0.2 ft for water level changes, 19.4 ft for vertical water level differences, −3.9 cubic feet per second (ft 3 /s) for drain discharges, 0.0 ft 3 /s for changes in drain discharge, 45.0 ft 3 /s for river seepage, −40.1 ft 3 /s for Lake Lowell seepage, and 126.3 ft 3 /s for changes in Lake Lowell seepage. The quality of the model’s fit to observations varied spatially, with notable areas of under- or over-simulation of water levels present to the northwest and southwest of Lake Lowell, in the foothills along the eastern model boundary, and near the City of Eagle. Trends were observed in the residuals of many of the observation groups, indicating that the model is missing or not fully reproducing some phenomena that are observed in the system. The TVGWFM can be used as a tool for water resource planning, for understanding the interactions of groundwater and surface water at a basin scale, and for facilitating conjunctive management, but may lack the precision needed for water rights administration at a local scale. Additional sources of uncertainty or limitations of the model are noted. The quantity and spatial distribution of canal seepage and infiltration of irrigation water recharge, the largest sources of recharge to the system, are unknown and approximated indirectly. There is poor understanding of how canal seepage and incidental recharge change as land is converted from agricultural (irrigated) to suburban (semi-irrigated). These uncertainties will affect any scenarios that investigate changes to land use or irrigation practices. Finally, the model has relatively high water-level residuals around and to the southwest of Lake Lowell and should not be used to estimate water level effects in that region. The model was built with multiple, broadly expressed objectives and did not optimize performance for specific uses. However, the model and the tools included in an associated data release provide ample flexibility to improve the model for future uses. Adjustments and improvements could be made by refining the model in an area of interest, collecting additional calibration data, applying more rigorous boundary conditions, or re-estimating model parameters to optimize model performance for a specific model forecast.

Idaho↗

The Borderlands and climate change: Chapter 10 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science

The prediction of global climate change in response to both natural forces and human activity is one of the defining issues of our times. The unprecedented observational capacity of modern earth-orbiting satellites coupled with the development of robust computational representations (models) of the Earth’s weather and climate systems afford us the opportunity to observe and investigate how these systems work now, how they have worked in the past, and how they will work in the future when forced in specific ways. In the most recent report on global climate change by the Intergovernmental Panel on Climate Change (IPCC; Solomon and others, 2007), analyses using multiple climate models support recent observations that the Earth’s climate is changing in response to a combination of natural and human-induced causes. These changes will be significant in the United States–Mexican border region, where the process of climate change affects all of the Borderlands challenge themes discussed in the preceding chapters. The dual possibilities of both significantly-changed climate and increasing variability in climate make it challenging to take full measure of the potential effects because the Borderlands already experience a high degree of interannual variability and climatological extremes.

United States-Mexico Borderlands↗

An epidemiological model of virus transmission in salmonid fishes of the Columbia River Basin

We have developed a dynamic epidemiological model informed by records of viral presence and genotypes to evaluate potential transmission routes maintaining a viral pathogen in economically and culturally important anadromous fish populations. In the Columbia River Basin, infectious hematopoietic necrosis virus (IHNV) causes severe disease, predominantly in juvenile steelhead trout ( Oncorhynchus mykiss ) and less frequently in Chinook salmon ( O. tshawytscha ). Mortality events following IHNV infection can be devastating for individual hatchery programs. Despite reports of high local mortality and extensive surveillance efforts, there are questions about how viral transmission is maintained. Modeling this system offers important insights into disease transmission in natural aquatic systems, as well as about the data requirements for generating accurate estimates about transmission routes and infection probabilities. We simulated six scenarios in which testing rates and the relative importance of different transmission routes varied. The simulations demonstrated that the model accurately identified routes of transmission and inferred infection probabilities accurately when there was testing of all cohort-sites. When testing records were incomplete, the model accurately inferred which transmission routes exposed particular cohort-sites but generated biased infection probabilities given exposure. After validating the model and generating guidelines for result interpretation, we applied the model to data from 14 annual cohorts (2000–2013) at 24 focal sites in a sub-region of the Columbia River Basin, the lower Columbia River (LCR), to quantify the relative importance of potential transmission routes in this focal sub-region. We demonstrate that exposure to IHNV via the return migration of adult fish is an important route for maintaining IHNV in the LCR sub-region, and the probability of infection following this exposure was relatively high at 0.16. Although only 1% of cohort-sites experienced self-exposure by infected juvenile fish, this transmission route had the greatest probability of infection (0.22). Increased testing and/or determining whether transmission can occur from cohort-sites without testing records (e.g., determining there was no testing record because there were no fish at the cohort-site) are expected to improve inference about infection probabilities. Increased use of secure water supplies and continued use of biosecurity protocols may reduce IHNV transmission from adult fish and juvenile fish within the site, respectively, to juvenile salmonids at hatcheries. Models and conclusions from this study are potentially relevant to understanding the relative importance of transmission routes for other important aquatic pathogens in salmonids, including the agents of bacterial kidney disease and coldwater disease, and the basic approach may be useful for other pathogens and hosts in other geographic regions.

Ecological Modelling↗

A reassessment of Chao2 estimates for population monitoring of grizzly bears in the Greater Yellowstone Ecosystem

The Yellowstone Ecosystem Subcommittee (YES) asked the Interagency Grizzly Bear Study Team (IGBST) to re-assess a technique used in annual population estimation and trend monitoring of grizzly bears in the Greater Yellowstone Ecosystem (GYE). This technique is referred to as the Chao2 approach and estimates the number of females with cubs-of-the-year (hereafter, females with cubs) and, in association with other demographic data, is used by the IGBST to produce annual population estimates. Females with cubs are an easily recognizable population segment, and trends for this reproductive segment of the population are assumed to be representative of trend for the entire population. The overarching objective of the analyses presented in this report was to provide a more accurate representation of the GYE grizzly bear population using the current methodologies in place. Specifically, we addressed two limitations of the current Chao2 approach: 1) underestimation bias associated with a distance criterion used to differentiate annual sightings of females with cubs into unique individuals and 2) limitations of the model-averaging approach to effectively distinguish among potential future population trajectories (decline, stability, and growth). The first issue addressed in this report is the underestimation bias associated with the rule set that Knight et al. (1995) developed to differentiate sightings of females with cubs into unique individuals (i.e., unique family groups). The rule set was originally designed to be conservative by reducing the risk of identifying more females with cubs than actually existed, primarily through use of a distance criterion of 30 km to separate sightings of unique females. This approach resulted in an underestimation bias, and previous research demonstrated that this bias increases with increasing number of females with cubs. Using location data from radio-marked females with cubs, we evaluated alternative distance criteria by simulating scenarios with varying numbers of true females with cubs and sightings. Findings from these analyses demonstrate that bias in estimates of females with cubs can be substantially reduced by changing the 30-km distance criterion in the rule set to 16 km, which produced relatively unbiased estimates. Findings also indicate, however, the importance of adaptability with regard to the distance criteria because of the complex relationships and biases among the various parameters involved in estimation of unique females with cubs. The total number of annual sightings and the true number of females with cubs play particularly important roles. Whereas these analyses remind us that there is no perfect approach to estimating the number of females with cubs from sightings under various scenarios, they provide us with new tools to determine when and how to adapt the monitoring program. The second issue we were tasked to investigate was the potential for improvement of the technique referred to as model-averaging, which serves to smooth relatively high variation in annual estimates. This technique was chosen by YES as the basis for monitoring the Yellowstone grizzly bear population, as described in the 2016 Conservation Strategy. This choice was made in part because the technique has been well documented and population estimates derived from counts of females with cubs are conservative. Using simulations of population trends, we demonstrate why the model-averaging technique currently used cannot distinguish between plausible future trend scenarios. As a suitable alternative to model averaging, we propose the use of generalized additive models (GAMs). Using a suite of simulated trend dynamics relevant to management, we demonstrate GAM performance for tracking trends in females with cubs within the context of the annual monitoring program. We demonstrate the ability to not only document directional changes in population trend but also patterns of stabilization or resiliency after such changes. Furthermore, the proposed monitoring framework provides objective measures useful for early detection of directional changes in trend. The new framework is flexible, allowing retrospective analysis of Chao2-based estimates and future applications to time series of other population metrics, such as vital rates. The aforementioned updates provide us with new tools to determine when and how to adapt the monitoring program. Within the context of current monitoring protocols and effort, and considering the full suite of simulations presented in this report and previous studies, the IGBST plans to incorporate the following changes to the population monitoring protocol: 1) modify the distance criterion, starting with 16 km under current sampling conditions and 2) revise the population monitoring framework using GAMs as the basis for smoothing of annual estimates and detecting trends and changes in trend. Implementation of the 16-km distance criterion combined with use of GAM techniques would affect some of the population metrics (e.g., annual population size and uncertainty, population trend, mortality rates) used to inform management responses. A primary consideration is that the 16-km distance criterion results in total population estimates derived from the Chao2 estimates that are greater than those we have reported in the past. This increase is due to a change in the implementation of the technique and more accurately represents the number of females with cubs in the GYE grizzly bear population. Additionally, interpretation of retrospective trend patterns may change due to the combination of a different distance criterion and enhanced trend monitoring based on the GAM approach we present here. Implementation will require relatively minor changes in the monitoring protocols described in Appendices B and C of the 2016 Conservation Strategy. Finally, we note that the IGBST has ongoing investigations into the merits of an Integrated Population Model (IPM), for which annual Chao2-based estimates are important input data. The IGBST plans to continue those investigations using the 16-km distance criterion to derive Chao2 estimates.

Idaho, Montana, Wyoming↗

Abundance estimation and conservation biology

Abundance is the state variable of interest in most population–level ecological research and in most programs involving management and conservation of animal populations. Abundance is the single parameter of interest in capture–recapture models for closed populations (e.g., Darroch, 1958; Otis et al., 1978; Chao, 2001). The initial capture–recapture models developed for partially (Darroch, 1959) and completely (Jolly, 1965; Seber, 1965) open populations represented efforts to relax the restrictive assumption of population closure for the purpose of estimating abundance. Subsequent emphases in capture–recapture work were on survival rate estimation in the 1970’s and 1980’s (e.g., Burnham et al., 1987; Lebreton et al.,1992), and on movement estimation in the 1990’s (Brownie et al., 1993; Schwarz et al., 1993). However, from the mid–1990’s until the present time, capture–recapture investigators have expressed a renewed interest in abundance and related parameters (Pradel, 1996; Schwarz & Arnason, 1996; Schwarz, 2001). The focus of this session was abundance, and presentations covered topics ranging from estimation of abundance and rate of change in abundance, to inferences about the demographic processes underlying changes in abundance, to occupancy as a surrogate of abundance. The plenary paper by Link & Barker (2004) is provocative and very interesting, and it contains a number of important messages and suggestions. Link & Barker (2004) emphasize that the increasing complexity of capture–recapture models has resulted in large numbers of parameters and that a challenge to ecologists is to extract ecological signals from this complexity. They offer hierarchical models as a natural approach to inference in which traditional parameters are viewed as realizations of stochastic processes. These processes are governed by hyperparameters, and the inferential approach focuses on these hyperparameters. Link & Barker (2004) also suggest that our attention should be focused on relationships between demographic processes such as survival and recruitment, the two quantities responsible for changes in abundance, rather than simply on the magnitudes of these quantities. They describe a type of Jolly–Seber capture–recapture model that permits inference about the underlying relationship between per capita recruitment rates and survival rates (Link & Barker, this volume). Implementation used Bayesian Markov Chain Monte Carlo methods and appeared to work well, yielding inferences about the relationship between recruitment and survival that were robust to selection of prior distribution. We believe that readers will find their arguments compelling, and we expect to see increased use of hierarchical modeling approaches in capture–recapture and related fields. Otto (presentation without paper) also recommended use of hierarchical models in analysis of multiple data sources dealing with population dynamics of North American mallards. He integrated survival inferences from ringing data, abundance information from aerial survey data, and recruitment information based on age ratios from a harvest survey. He used a Leslie matrix population projection model as an integrating framework and obtained estimates of breeding population size using all data.Otto’s approach also permitted inference about biases in estimated quantities. As with the work of Link & Barker (2004), we find Otto’s recommendation to use hierarchical models to integrate data from multiple sources to be very compelling. Alisauskas et al. (2004) report results of an analysis of capture–recapture data for a askatchewan population of white–winged scoters. They used the approach of Pradel (1996) to estimate population growth rate (See the PDF) directly. Estimates for 1975–1985 were quite low, but estimates for the recent period, 2000–2003,increased to values > 1. Parameter estimates for seniority, survival and per capita recruitment (Pradel, 1996) led to the inference that increased recruitment was largely responsible for the improvements in population status and growth. However, various data sources also indicated that this increase in recruitment was likely a result of increased immigration rather than improved reproduction on the area. This latter inference is important from a conservation perspective in indicating the importance of birds in other locations to growth and health of the study population. Lukacs and Burnham presented material to be published elsewhere that dealt with the use of genetic markers in capture–recapture studies. The data sources for such studies are samples of hair or feces, which are then analyzed using molecular genetic techniques in order to determine individual genotypes with respect to a usually small number of loci. Two types of classification error can arise in such analyses. First, if only a small number of loci is examined, then there may be nonnegligible probabilities that multiple individual animals will have the same genotypes. The second type of error arises during the polymerase chain reaction (PCR) process and can result from failure of alleles to amplify (allelic dropout) or from PCR inhibitors in hair and feces that produce the appearance of false alleles or misprinting (Creel et al., 2003). Lukacs and Burnham developed models that formally incorporate possible misclassification of samples resulting from these errors. These models permit estimation of parameters such as abundance and survival in a manner that properly incorporates this uncertainty of individual identity. We anticipate that noninvasive sampling based on molecular genetic analyses of hair or feces will become extremely important for some species, and that the models of Lukacs and Burnham will become very popular for such analyses. MacKenzie & Nichols (2004) discuss the use of occupancy (proportion of patches or habitat area that is occupied) as a surrogate for abundance. In cases of territorial species and where birds occur at low densities, the number of occupied patches may provide a reasonable estimate of abundance. In other cases, occupancy can be viewed as providing information about one tail of the abundance distribution, P (N = 0). The motivation for considering occupancy as a surrogate for abundance is that occupancy is based on so–called presence–absence surveys that are frequently less expensive of time and effort than methods that estimate abundance directly. We describe one set of models that can be used to estimate occupancy for a single season and another that can be used to estimate parameters such as local probabilities of extinction and colonization that are associated with occupancy dynamics. We outline a possible hybrid approach that combines occupancy data with data on marked individuals in order to betterexplore the mechanisms underlying occupancy dynamics. These five presentations made for an interesting session containing useful information and recommendations for future work. A number of themes connecting these presentations could be emphasized. For example, two of the presentations considered alternatives to standard capture–recapture sampling that can be used to draw inferences about abundance, or a portion of the abundance distribution, with field methods that should be less expensive than usual capture–recapture approaches of handling animals. We believe that the most important theme of the session was the emphasis on the processes responsible for changes in abundance. In particular, we are excited by the potential for using hierarchical models as a means of investigating relationships among vital rates and as a means of combining multiple sources of data relevant to system dynamics. Indeed, we expect the importance of this session theme to be reflected in the content and presentations of the next EURING meeting.

Animal Biodiversity and Conservation↗

An interim report on flows in the lower Roanoke River, and water quality and hydrodynamics of Albermarle Sound, North Carolina, October 1989-April 1991

In 1990, a 3-year investigation was begun in North Carolina to: (1) develop a model for computing flows in the lower 67 mi of the Roanoke River; (2) characterize water-quality conditions in Albemarle Sound; and (3) describe the circulation regime of Albemarle Sound, particularly in relation to inflows. This report summarizes data and results obtained during the first year of the study. The water level in Albemarle Sound may affect flows in the Roanoke River as far as 60 mi upstream from the mouth of the river. The presence of higher water levels downstream relative to those upstream indicates that reverse flows likely occurred in the lower 20 mi of the Roanoke River in October and December 1990. A one-dimensional, unsteady flow model has been calibrated and validated for a 30-mi segment of the lower Roanoke River. Simulated and observed water levels typically differed by less than 0.5 ft, and simulated flows were generally within 10% of observed values. Near-surface and near-bottom specific conductances, near-surface water temperature, and near-surface, mid-depth, and near-bottom dissolved-oxygen concentrations were monitored at 10 locations in Albemarle Sound from October 1989 to April 1991. Observed salinities ranged from virtually 0 to more than 9 ppt, and maximum observed water temperatures were about 32C. Dissolved oxygen concentrations ranged from supersaturated to hypoxic conditions. The daily range in dissolved-oxygen concentrations was typically larger during the summer months than during the rest of the year, and the lowest dissolved-oxygen values were observed during the summer.

North Carolina↗

SMSIM--Fortran programs for simulating ground motions from earthquakes: Version 2.0.--a revision of OFR 96-80-A

A simple and powerful method for simulating ground motions is based on the assumption that the amplitude of ground motion at a site can be specified in a deterministic way, with a random phase spectrum modified such that the motion is distributed over a duration related to the earthquake magnitude and to distance from the source. This method of simulating ground motions often goes by the name "the stochastic method." It is particularly useful for simulating the higher-frequency ground motions of most interest to engineers, and it is widely used to predict ground motions for regions of the world in which recordings of motion from damaging earthquakes are not available. This simple method has been successful in matching a variety of ground-motion measures for earthquakes with seismic moments spanning more than 12 orders of magnitude. One of the essential characteristics of the method is that it distills what is known about the various factors affecting ground motions (source, path, and site) into simple functional forms that can be used to predict ground motions. SMSIM is a set of programs for simulating ground motions based on the stochastic method. This Open-File Report is a revision of an earlier report (Boore, 1996) describing a set of programs for simulating ground motions from earthquakes. The programs are based on modifications I have made to the stochastic method first introduced by Hanks and McGuire (1981). The report contains source codes, written in Fortran, and executables that can be used on a PC. Programs are included both for time-domain and for random vibration simulations. In addition, programs are included to produce Fourier amplitude spectra for the models used in the simulations and to convert shear velocity vs. depth into frequency-dependent amplification. The revision to the previous report is needed because the input and output files have changed significantly, and a number of new programs have been included in the set.

Open-File Report↗

Klamath River Water Quality Data from Link River Dam to Keno Dam, Oregon, 2008

This report documents sampling and analytical methods and presents field data from a second year of an ongoing study on the Klamath River from Link River Dam to Keno Dam in south central Oregon; this dataset will form the basis of a hydrodynamic and water quality model. Water quality was sampled weekly at six mainstem and two tributary sites from early April through early November, 2008. Constituents reported herein include field-measured water-column parameters (water temperature, pH, dissolved oxygen concentration, specific conductance); total nitrogen and phosphorus; particulate carbon and nitrogen; total iron; filtered orthophosphate, nitrite, nitrite plus nitrate, ammonia, organic carbon, and iron; specific UV absorbance at 254 nanometers; chlorophyll a; phytoplankton and zooplankton enumeration and species identification; and bacterial abundance and morphological subgroups. Sampling program results indicated: *Most nutrient and carbon concentrations were lowest in spring, increased starting in mid-June, remained elevated in the summer, and decreased in fall. Dissolved nitrite plus nitrate had a different seasonal cycle and was below detection or at low concentration in summer. *Although total nitrogen and total phosphorus concentrations did not show large differences from upstream to downstream, filtered ammonia and orthophosphate concentrations increased in the downstream direction and particulate carbon and particulate nitrogen generally decreased in the downstream direction. *Large bacterial cells made up most of the bacteria biovolume, though cocci were the most numerous bacteria type. Cocci, with diameters of 0.1 to 0.2 micrometers, were smaller than the filter pore sizes used to separate dissolved from particulate matter. *Phytoplankton biovolumes were dominated by diatoms in spring and by the blue-green alga Aphanizomenon flos-aquae after mid-June. Another blue-green, Anabaena flos-aquae, was noted in samples from late May to late June. Phytoplankton biovolumes generally were highest at the upstream Link River and Railroad Bridge sites and decreased in the downstream direction. *Zooplankton densities were largest in late April. Populations were dominated by rotifers and copepods in early spring, and by rotifers and cladocerans in summer, with cladocerans most common at the most upstream site.

Open-File Report↗