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Ecoregions of California

Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across Federal agencies, State agencies, and nongovernment organizations that are responsible for different types of resources in the same geographical areas (Omernik and others, 2000). The approach used to compile this map is based on the premise that ecological regions are hierarchical and can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997, map revised 2006). At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions (U.S. Environmental Protection Agency, 2013). Level IV, depicted here for California, is a further refinement of level III ecoregions. Explanations of the methods used to define these ecoregions are given in Omernik (1995), Omernik and others (2000), and Omernik and Griffith (2014). California has great ecological and biological diversity. The State contains offshore islands and coastal lowlands, large alluvial valleys, forested mountain ranges, deserts, and various aquatic habitats. There are 13 level III ecoregions and 177 level IV ecoregions in California and most continue into ecologically similar parts of adjacent States of the United States or Mexico (Bryce and others, 2003; Thorson and others, 2003; Griffith and others, 2014). The California ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale (Omernik, 1987; U.S. Environmental Protection Agency, 2013). This poster is the result of a collaborative project primarily between U.S. Environmental Protection Agency (USEPA) Region IX, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), California Department of Fish and Wildlife (DFW), U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), U.S. Department of the Interior–Geological Survey (USGS), and other State of California agencies and universities. The project is associated with interagency efforts to develop a common framework of ecological regions (McMahon and others, 2001). Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service (Bailey and others, 1994; Miles and Goudy, 1997; Cleland and others, 2007), the USEPA (Omernik 1987, 1995), and the NRCS (U.S. Department of Agriculture–Soil Conservation Service, 1981; U.S. Department of Agriculture–Natural Resources Conservation Service, 2006). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in California, where some agreement has been reached among multiple resource-management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.

California↗

A case for using Plethodontid salamanders for monitoring biodiversity and ecosystem integrity of North American forests

Terrestrial salamanders of the family Plethodontidae have unique attributes that make them excellent indicators of biodiversity and ecosystem integrity in forested habitats. Their longevity, small territory size, site fidelity, sensitivity to natural and anthropogenic perturbations, tendency to occur in high densities, and low sampling costs mean that counts of plethodontid salamanders provide numerous advantages over counts of other North American forest organisms for indicating environmental change. Furthermore, they are tightly linked physiologically to microclimatic and successional processes that influence the distribution and abundance of numerous other hydrophilic but difficult-to-study forest-dwelling plants and animals. Ecosystem processes such as moisture cycling, food-web dynamics, and succession, with their related structural and microclimatic variability, all affect forest biodiversity and have been shown to affect salamander populations as well. We determined the variability associated with sampling for plethodontid salamanders by estimating the coefficient of variation (CV ) from available time-series data. The median coefficient of variation indicated that variation in counts of individuals among studies was much lower in plethodontids (27%) than in lepidoptera (93%), passerine birds (57%), small mammals (69%), or other amphibians (37–46%), which means plethodontid salamanders provide an important statistical advantage over other species for monitoring long-term forest health.

Conservation Biology↗

Santa Barbara and Foothill groundwater basins Geohydrology and optimal water resources management—Developed using density dependent solute transport and optimization models

Groundwater has been a part of the city of Santa Barbara’s water-supply portfolio since the 1800s; however, since the 1960s, the majority of the city’s water has come from local surface water, and the remainder has come from groundwater, State Water Project, recycled water, increased water conservation, and as needed, seawater desalination. Although groundwater from the Santa Barbara and Foothill groundwater basins only accounts for a small percentage of the long-term supply, it is an important source of supplemental water during times of surface-water shortages. During the late 1980s and early 1990s, production wells extracted additional groundwater to compensate for drought related water-delivery shortfalls from other sources; in response, water levels declined substantially in the Santa Barbara and Foothill groundwater basins (below sea level in the Santa Barbara groundwater basin). In coastal basins that have groundwater extraction near shore, seawater intrusion is often a problem. Seawater intrusion in the Santa Barbara groundwater basin is thought to be more limited than in other coastal basins because of an offshore fault that acts as a partial barrier to groundwater flow. During the late 1980s and early 1990s, seawater intrusion was observed in the Santa Barbara groundwater basin, as indicated by increased chloride concentrations at several monitoring wells that ranged from 200 ft to 1,300 ft from the ocean and as close as 2,900 ft to the nearest pumping well. This demonstrated that seawater can intrude into the Santa Barbara groundwater basin when groundwater levels fall below sea level near the coast. The city of Santa Barbara is interested in developing a better understanding of the sustainability of its groundwater supplies. In 2014, California adopted historic legislation to manage its groundwater: the Sustainable Groundwater Management Act (SGMA). The SGMA requires the development and implementation of “Groundwater Sustainability Plans” in 127 priority groundwater basins; although Santa Barbara was not a designated priority basin, the city is taking steps to achieve sustainability. Sustainability was defined in the SGMA in terms of avoiding undesirable results: significant and unreasonable groundwater-level declines, reduction in groundwater storage, seawater intrusion, water-quality degradation, land subsidence, and surface-water depletion. In this project, a cooperative study between the U.S. Geological Survey (USGS) and the city of Santa Barbara, sustainable yield is defined as the volume of groundwater that can be pumped from storage without causing water-level drawdowns and the associated increases in seawater intrusion (as indicated by increases in measured chloride concentrations) at selected wells. In order to estimate the sustainability of Santa Barbara’s groundwater basins, a three-dimensional density-dependent groundwater-flow and solute-transport model (the Santa Barbara Flow and Transport Model, or SBFTM) was developed on the basis of an existing groundwater-flow model. To simulate seawater intrusion to the Santa Barbara Basin under various management strategies, the SBFTM uses the USGS code SEAWAT to simulate salinity transport and variable-density flow. The completed SBFTM was coupled with a management optimization tool, in this case a multi-objective evolutionary algorithm, to determine optimal pumping strategies that maximize the sustainable yield and at the same time satisfy user-defined drawdown and chloride-concentration constraints. As part of this study, a three-dimensional hydrogeologic framework model was developed to quantify the extent and hydrogeologic characteristics of the Santa Barbara and Foothill groundwater basins and to help define the discretization and hydraulic properties used in the SBFTM. The development of the hydrogeologic framework model required the collection and reconciliation of geologic and geophysical data from existing maps, reports, and databases, along with geologic and hydrologic data from recently drilled wells. These data were integrated into a three-dimensional hydrogeologic framework model that defines the stratigraphy and geometry of the aquifer zones and the major geologic structures in the basin. The hydrogeologic framework model also quantifies the variation in sediment grain size within each aquifer zone as the percentage of coarse-grained sediment. Previous studies indicated that there are two principal water-producing zones in the Santa Barbara groundwater basin, the upper and lower producing zones; an additional thin, productive zone was identified as part of this study. This “middle producing zone” is not as areally extensive as the upper and lower producing zones and only exists in the coastal part of Storage Unit I. These producing zones are bounded at depth by less productive shallow, middle, and deep zones. Two versions of the SBFTM were constructed: an initial-condition model and a modern transient model. The initial-condition model is a long-term transient model that simulates flow and solute-transport conditions during a period with limited anthropogenic influences preceeding the modern transient model. The simulation-transient model simulates flow and transport conditions from 1929 through 2013; however, because of data availability, the focus of the model calibration was 1972–2013. The SBFTM was calibrated to measured groundwater levels and drawdown, as well as measured chloride concentrations and change in concentrations, using a combination of automated and trial-and-error parameter-estimation techniques. A sensitivity analysis indicated that, in general, the SBFTM was most sensitive to recharge- and pumping-distribution parameters, specifically those controlling the amount of small-catchment recharge and the distribution of water extraction by hydrogeologic layer for production wells. The model was also sensitive to parameters controlling stream-recharge rates, horizontal and vertical hydraulic conductivity, and porosity. From 1929 to 1971, most of the water entering the area represented by the SBFTM was from creek and small-catchment recharge, and the majority of water leaving the SBFTM area was from pumping, discharge to creeks, and drains. In addition, about 37 percent of the total pumpage came from a net reduction in groundwater storage. From 1972 to 2013, the amount of water entering and leaving the SBFTM was fairly similar as that from 1929 to 1971, except the reduction in pumpage added about 17,000 acre-ft of water to storage. During this later period, there were also times of storage loss. For example, during July 1990, a month when approximately 705 acre-ft of groundwater was pumped in the study area, the pumpage was much greater than all sources of recharge combined, and about 382 acre-ft of water was removed from groundwater storage. Simulated hydraulic heads replicated the observed data to an acceptable matching of the measured water-level, flow direction, and vertical gradients. Simulated hydrographs for selected wells were in good agreement with the measured data, with an average residual of -2.7 ft and a standard deviation of 14.5 ft, indicating that the simulated heads, on average, underestimated the observed water levels. An examination of the model fit indicated that most of the discrepancies were lower simulated heads at wells proximal to production well sites. The simulated chloride concentrations reasonably matched the rising limbs of the measured breakthrough curves in terms of timing and magnitude; however, the simulation overestimated the chloride concentrations on the falling limbs. The overestimation of low chloride concentrations was attributed to the model overestimating the advance of the chloride front during periods of heavy pumping and underestimating the retreat of the chloride front during periods of low pumping. These simulation errors would result in a conservative response by local water managers to seawater intrusion. The SBFTM was used to develop a collection of predictive simulations optimized to produce pumping schedules that maximize yield, subject to a set of constraints and competing objectives. The simulations were grouped as scenarios that differed in their time horizon, initial conditions for groundwater levels and chloride concentrations, as well as precipitation, which was incorporated into the model through simulated recharge. Overall, five scenarios were developed in a multi-objective framework to obtain optimal pumping rates for all of the wells managed by the city, while minimizing excessive drawdown and seawater intrusion. For the current study, complexities in the simulation model and the optimization formulation required additional considerations. Incorporating the solute-transport equations to simulate chloride transport added a highly nonlinear process that is solved iteratively in each time step of the groundwater-flow model. These nonlinearities, coupled with the highly refined grid in the current model, creates challenges for many traditional optimization methods. Therefore, an optimization method was needed that could address nonlinear relationships as well as a very large problem size. Lastly, the optimization problem was reformulated to include multiple objectives without requiring convergence to a single solution. This approach, guided by the city’s objectives, allowed the maximum extraction of information from the complex simulation. Borg, a multi-objective evolutionary algorithm, was chosen as the optimization algorithm for this study for several reasons: (1) it is very computationally efficient; (2) it can run in parallel; (3) it requires little user input; and (4) it can solve for multiple competing objectives. The first three points allow the algorithm to proceed toward the optimal solutions at the fastest possible rate. The fourth point is advantageous for large, complex optimization problems because it is difficult to formulate the optimization problem in a way that produces only one optimal solution. The problem formulation consisted of four competing objectives and a constraint set in accordance with the main concerns of the city. The objectives were maximizing total pumpage, minimizing seawater intrusion, minimizing total drawdown in production wells, and minimizing the maximum drawdown. The constraints were pump capacity, meeting drinking-water standards for chloride, maintaining a specified minimum flowrate to a groundwater treatment plant, and maintaining minimum water levels in pumping wells. The decision variables either were quarterly pumpage by well or total pumpage by basin. Five optimization scenarios were developed that allow the decision makers to evaluate a range of optimal solutions for a variety of water levels and chloride concentrations as well as potential future climatic conditions. Three scenarios (1, 2, and 5) were multi-objective optimization formulations that allowed for variations in management preferences and climatic conditions. The other two scenarios (3 and 4) were designed to examine the optimization results to answer specific questions. Scenario 1 described the best-case sustainable yield assuming a “full” basin (that is, high initial water levels) and typical climate conditions for 10 years. Scenario 2 also started with a “full” basin; however, this was followed by a 10-year drought. Scenario 3 determined if an “empty” basin (that is, low initial water levels) would recover to full conditions (1998 conditions) given climate assumptions and optimal pumping schedules from scenarios 1 and 2. Scenario 4 was designed to produce decision rules that can be used by water managers to help choose an optimal pumping schedule based on measured water-level or chloride data. Scenario 5 identified future pumping schedules based on short-term climate variations during a 2-year management horizon. The results from scenarios 1 and 2 described the differences in maximum pumpage in the basin under typical and dry long-term climate projections, respectively. The scenario 1 results indicated the maximum 10-year pumpage of the basin was about 31,300 acre-ft under typical conditions and controlling simulated seawater intrusion and drawdowns. For scenario 2, less recharge over the 10-year dry climate produced a maximum pumpage estimate of 30,000 acre-ft to control seawater intrusion and drawdowns. The larger pumpage for scenario 1 resulted in more seawater intrusion, but less total drawdown, compared to that of scenario 2. Results for scenarios 3 and 4 showed the basin’s response to management actions combined with climate projections. Both scenarios used the optimal pumping schedules and the 10-year climates from scenarios 1 and 2. The scenario 3 results showed that under minimal pumping, the basin did not fully recover to 1998 water levels within 10 years under either climate scenario. The relatively larger recharge from the typical climate resulted in less drawdown at coastal monitoring wells after the 10-year recovery period than that from the dry climate. The location of the seawater intrusion front was not appreciably different between the scenarios, however. Scenario 4 used the optimal results from scenarios 1 and 2 to produce decision-rule curves that illustrated the pumpage for each basin, given measured levels of chloride concentration or drawdown. This allowed the use of additional measurements at monitoring wells to assess future management decisions on the basis of the sensitivity of observations of drawdown and seawater intrusion to various pumping rates. Scenario 5 allowed managers to investigate the effects of short-term climate variations on optimal pumping schedules. Three specific 2-year simulations were optimized: typical-to-dry (scenario 5A), dry-to-typical (scenario 5B), and dry-to-dry (scenario 5C). The most noteable result from scenario 5 was the overall reduction in optimal pumpage for most schedules in scenario 5C, when the climate is simulated as dry-to-dry. There are also many optimal pumping schedules that produced an overall increase in waterlevels over the two-year simulation period, regardless of climatic condition. Similar to scenario 2, the scenario 5C results represents conservative yield estimates under a minimal-precipitation climatic condition.

California↗

Forecasting the combined effects of urbanization and climate change on stream ecosystems: from impacts to management options

Streams collect runoff, heat, and sediment from their watersheds, making them highly vulnerable to anthropogenic disturbances such as urbanization and climate change. Forecasting the effects of these disturbances using process-based models is critical to identifying the form and magnitude of likely impacts. Here, we integrate a new biotic model with four previously developed physical models (downscaled climate projections, stream hydrology, geomorphology, and water temperature) to predict how stream fish growth and reproduction will most probably respond to shifts in climate and urbanization over the next several decades. The biotic submodel couples dynamics in fish populations and habitat suitability to predict fish assemblage composition, based on readily available biotic information (preferences for habitat, temperature, and food, and characteristics of spawning) and day-to-day variability in stream conditions. We illustrate the model using Piedmont headwater streams in the Chesapeake Bay watershed of the USA, projecting ten scenarios: Baseline (low urbanization; no on-going construction; and present-day climate); one Urbanization scenario (higher impervious surface, lower forest cover, significant construction activity); four future climate change scenarios [Hadley CM3 and Parallel Climate Models under medium-high (A2) and medium-low (B2) emissions scenarios]; and the same four climate change scenarios plus Urbanization. Urbanization alone depressed growth or reproduction of 8 of 39 species, while climate change alone depressed 22 to 29 species. Almost every recreationally important species (i.e. trouts, basses, sunfishes) and six of the ten currently most common species were predicted to be significantly stressed. The combined effect of climate change and urbanization on adult growth was sometimes large compared to the effect of either stressor alone. Thus, the model predicts considerable change in fish assemblage composition, including loss of diversity. Synthesis and applications . The interaction of climate change and urban growth may entail significant reconfiguring of headwater streams, including a loss of ecosystem structure and services, which will be more costly than climate change alone. On local scales, stakeholders cannot control climate drivers but they can mitigate stream impacts via careful land use. Therefore, to conserve stream ecosystems, we recommend that proactive measures be taken to insure against species loss or severe population declines. Delays will inevitably exacerbate the impacts of both climate change and urbanization on headwater systems.

Journal of Applied Ecology↗

Time-domain electromagnetic soundings and passive-seismic measurements for delineation of saline groundwater in the Genesee Valley-fill aquifer system, western New York, 2016–17

The U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, used noninvasive surface geophysics in the investigation of the distribution of saline groundwater in the valley-fill aquifer system of the Genesee River Valley near the former Retsof salt mine in western New York. In 1994, the Retsof salt mine, the largest of its kind in the western hemisphere, underwent a catastrophic roof collapse that resulted in groundwater inflow from the valley-fill aquifer system and bedrock fracture zones into the mine through two bedrock-rubble chimneys and the subsequent dissolution and filling of the mine with saturated brine. Since the early 2000s, except for a period of remedial pumping in 2006 to 2013, high-salinity water has migrated upward through the rubble chimneys into the basal part the aquifer system. The extent of saline-water migration within the aquifer system had not been evaluated since the end of remedial pumping when all the monitoring wells were grouted shut and abandoned. Installation of a monitoring-well network would be expensive and difficult given the thickness and heterogeneous character of valley fill. An investigation of the current extent of saline water in the aquifer system was warranted because the basal part of the aquifer is shallow to the north and it is used for water supply. In fall 2016 and fall 2017, the U.S. Geological Survey collected time-domain electromagnetic soundings at 105 sites along 13 cross-valley transects north and south of the mine-collapse area, east of Piffard, and on the Fowlerville Moraine. The time-domain electromagnetic soundings were colocated with passive-seismic measurements to estimate the bedrock-surface elevation through use of a regression equation developed from measurements at well sites with reported bedrock depths in the study area. An integrated analysis of the time-domain electromagnetic soundings with the depth-to-bedrock estimates, well logs, and past chloride-monitoring data suggests the presence of a zone of high electrical conductivity associated with saline water in the confined lower part of the valley-fill aquifer system. This high-salinity zone delineated in the lower confined aquifer extends from the mine-collapse area northward for more than 2.5 miles (4.0 kilometers). The chloride concentration in groundwater within this high-conductivity zone may be about 20,000 milligrams per liter. Saline water flowing upward through the bedrock-rubble chimneys and mixing with northward groundwater flow in the lower confined aquifer likely is a major source of chlorides for this high-conductivity zone. The northern extent of the zone is unclear because of the presence of highly saline water zones that were delineated by time-domain electromagnetic soundings in the lower confined aquifer and uppermost bedrock and are probably associated with historic salt-solution wells in Piffard or possibly sourced from natural brine pools.

New York↗

Patterns of water-extractable soil organic matter in the US Great Plains: Insights from the Haas Soil Archive

Novel approaches that are fast and sensitive are needed to evaluate soil change and integrate soil ecosystem properties. Carbon (C) and nitrogen (N) extracted from soil with water are associated with plant nutrients and microbial activity but information about change over time in the US Great Plains is sparse. We used cool (20°C) and hot (80°C) water extracts from historic (1947) and contemporary (2018) soil samples collected at Moccasin, MT; Akron, CO; and Big Spring, TX; to examine changes to labile C and N and optical properties after 71 years of dryland cropping. Concentrations of C and N extracted with cool water decreased between 1947 and 2018 in surface (0–15.2 cm) samples from Moccasin, by 52% and 35%, and Big Spring, by 37% and 32%, but remained unchanged at Akron. Conversely, net (hot−cool) extractable C did not change at Moccasin or Big Spring but increased at Akron by 26%. Net extractable N decreased at Moccasin by 22% but did not change elsewhere. Sequential principal component analysis and stepwise discriminant analysis identified three important optical properties. Values of SUVA 254 (where SUVA 254 is the specific ultraviolet absorbance at 254 nm) in extracts did not change at Moccasin between 1947 and 2018 but increased at Akron, indicating increased aromaticity. Conversely, SUVA 254 decreased at Big Spring. Values for Sag 350–400 (where Sag 350–400 is the slope from a nonlinear fit of an exponential function to the absorption spectrum over the wavelength range from 350 to 400 nm), inversely related to extract molecular weight and aromaticity, decreased at Moccasin but not elsewhere. The proportion of recalcitrant to labile compounds, C:T (where C:T is the ratio of fluorescence intensity from Peak C [ex340/em440] to Peak T [ex275/em340]), increased in extracts from all sites but especially at Akron. Together, these methods provided insights into soil change while conserving samples.

Colorado, Kansas, Montana, Nebraska, New Mexico, N↗

Graphic comparison of reserve-growth models for conventional oil and accumulation

The U.S. Geological Survey (USGS) periodically assesses crude oil, natural gas, and natural gas liquids resources of the world. The assessment procedure requires estimated recover-able oil and natural gas volumes (field size, cumulative production plus remaining reserves) in discovered fields. Because initial reserves are typically conservative, subsequent estimates increase through time as these fields are developed and produced. The USGS assessment of petroleum resources makes estimates, or forecasts, of the potential additions to reserves in discovered oil and gas fields resulting from field development, and it also estimates the potential fully developed sizes of undiscovered fields. The term ?reserve growth? refers to the commonly observed upward adjustment of reserve estimates. Because such additions are related to increases in the total size of a field, the USGS uses field sizes to model reserve growth. Future reserve growth in existing fields is a major component of remaining U.S. oil and natural gas resources and has therefore become a necessary element of U.S. petroleum resource assessments. Past and currently proposed reserve-growth models compared herein aid in the selection of a suitable set of forecast functions to provide an estimate of potential additions to reserves from reserve growth in the ongoing National Oil and Gas Assessment Project (NOGA). Reserve growth is modeled by construction of a curve that represents annual fractional changes of recoverable oil and natural gas volumes (for fields and reservoirs), which provides growth factors. Growth factors are used to calculate forecast functions, which are sets of field- or reservoir-size multipliers. Comparisons of forecast functions were made based on datasets used to construct the models, field type, modeling method, and length of forecast span. Comparisons were also made between forecast functions based on field-level and reservoir- level growth, and between forecast functions based on older and newer data. The reserve-growth model used in the 1995 USGS National Assessment and the model currently used in the NOGA project provide forecast functions that yield similar estimates of potential additions to reserves. Both models are based on the Oil and Gas Integrated Field File from the Energy Information Administration (EIA), but different vintages of data (from 1977 through 1991 and 1977 through 1996, respectively). The model based on newer data can be used in place of the previous model, providing similar estimates of potential additions to reserves. Fore-cast functions for oil fields vary little from those for gas fields in these models; therefore, a single function may be used for both oil and gas fields, like that used in the USGS World Petroleum Assessment 2000. Forecast functions based on the field-level reserve growth model derived from the NRG Associates databases (from 1982 through 1998) differ from those derived from EIA databases (from 1977 through 1996). However, the difference may not be enough to preclude the use of the forecast functions derived from NRG data in place of the forecast functions derived from EIA data. Should the model derived from NRG data be used, separate forecast functions for oil fields and gas fields must be employed. The forecast function for oil fields from the model derived from NRG data varies significantly from that for gas fields, and a single function for both oil and gas fields may not be appropriate.

Bulletin↗

Human influence on California fire regimes

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation. ?? 2007 by the Ecological Society of America.

Ecological Applications↗

Environmental drivers of productivity explain population patterns of an Arctic-nesting goose across a half-century

Joint estimation of demographic rates and population size has become an essential tool in ecology because it enables evaluating mechanisms for population change and testing hypotheses about drivers of demography in a single modeling framework. This approach provides a comprehensive perspective on population dynamics and how animal populations will respond to global pressures in future years. However, long-term data for such analyses are often limited in quantity and quality. We developed an integrated population model combining data on demography and population size from nine different sources to understand the population ecology of the lesser snow goose ( Anser caerulescens caerulescens ) in the Pacific Flyway in North America from 1970 to 2022. We divided the flyway population into Wrangel Island and Western Arctic subpopulations and assessed demographic mechanisms for population change and environmental and anthropogenic drivers that influenced demography. During 1970–2022, the estimated spring population of snow geese in the Pacific Flyway increased from ~300,000 to ~2,300,000. Short-term changes in population growth rate were primarily driven by changes in productivity in the Western Arctic and productivity and immigration in Wrangel Island. Changes in hunting and natural mortality had less influence on short-term but likely contributed to the pronounced long-term population growth. Early snowmelt positively influenced per capita productivity in both regions, and warm, rainy weather during the non-breeding season was associated with high per capita productivity in the Western Arctic. In the Western Arctic, per capita productivity was negatively associated with population size, and adult natural mortality was positively associated with population size, indicating density-dependent regulation in this subpopulation. In Wrangel Island, warm weather in early fall decreased juvenile natural mortality. Our results demonstrate that per capita productivity and immigration, rather than adult survival, were the primary mechanisms of short-term population change in this long-lived species. Our results also indicate that environmental conditions and density-dependent effects can impact population dynamics more than harvest, even for a long-lived, commonly harvested species. We demonstrate that a warming climate can have multiple effects on demography, emphasizing the importance of assessing a variety of spatial and temporal factors when predicting how populations might respond to large-scale environmental changes. This emphasizes the importance of conservation plans that consider these environmental drivers, although this may complicate direct management of such populations.

Ecological Applications↗

Status assessment of peregrine falcons in North America using integrated population models

Species status assessments require an understanding of underlying population dynamics and important drivers of species demography. Large-scale assessments can be difficult due to challenges collating data obtained through different methods and different sources at multiple scales. Integrated population models (IPMs) provide a unified framework to combine multiple data sources and jointly estimate population parameters over a large spatiotemporal scale. We developed separate IPMs to estimate abundance and demographic rates for a northern (NMP) and southern (SMP) management population of peregrine falcons ( Falco peregrinus ) in North America from 2008 through 2019 (SMP) and 2020 (NMP). An outbreak of highly pathogenic avian influenza (HPAI) starting in 2021 led us to extend our modeling effort to assess its impact on these management populations by updating both IPMs using index data of population size through 2024 in a predictive framework. Survival probabilities differed drastically between first-year and after-first-year individuals in both management populations. After-first-year survival was nearly identical between the NMP and SMP, but first-year survival was lower in the SMP. Mean productivity was significantly lower in the NMP compared to the SMP, whereas the probability of breeding was similar in both management populations. Estimated total abundance for the NMP was substantially larger than the SMP, representing most of the North American peregrine population. Population growth was positive for both management populations, albeit at a slower rate for the NMP. The NMP declined from 2017 to 2018 coinciding with a drop in 2018 estimated productivity. When we extended the IPMs with updated count data through 2024, the NMP slightly declined but estimated abundance remained above levels at the start of the time series analyzed. The SMP grew at a similar rate to that predicted during the period informed by demographic data. We did not detect a continental-scale change in population size or trajectory in either management population associated with the arrival of HPAI in 2021. Further monitoring can support determination of whether the declines in the NMP were temporary, can enhance understanding of the underlying mechanisms, and can be used to guide the conservation and management of the peregrine falcon population in North America.

North America↗

Wildlife values of North American ricelands

Ricelands have become an indispensable component of waterbird habitat and a leading example of integrating agricultural and natural resource management in the Mississippi Alluvial Valley, Gulf Coast, and Central California. Residual rice, weed seeds, and invertebrates provide food for many avian species during fall and winter. In North America, considerable information exists on the use of ricefields by wintering waterbirds, the value of ricelands as breeding habitat for birds, and the effects of organic chemicals on birds that- feed in ricefields. Recent research has also examined the influence of field management practices, such as winter flooding and post-harvest straw manipulation, on the suitability of ricefields for wildlife. Whereas early studies focused on detrimental effects of wildlife on rice production (e.g., crop depredation), it has become apparent that waterbirds may benefit producers by enhancing straw decomposition, reducing weed and pest pressure, and providing additional income through hunting and wildlife viewing opportunities. A comprehensive evaluation of agronomic and environmental issues is needed to meet the challenges of producing food and sustaining wildlife in twenty-first-century rice lands. Changes in agricultural markets, pressures of increased urban development, conflicting needs for limited resources such as water, endangered species constraints, and concerns over water quality must be addressed in developing a sustainable, mutually beneficial partnership among the rice industry, wildlife, and environmental interests. Research is also needed to evaluate potential reductions in the wildlife carrying capacity of ricelands resulting from new harvest and field management techniques, crop conversion, or loss of rice acreage. Key uncertainties include: (1) changes in waste grain abundance and availability due to various harvest and post-harvest management practices; (2) evaluating food depletion by birds feeding in rice6elds and derermining threshold food levels required to maintain bird use; (3) quantifying use of ricefields by nonwaterfowl species throughout the year; and (4) determining the amount and distribution of rice habitat needed to meet objectives of the North American Waterfowl Management Plan and the United States Shorebird Conservation Plan.

Book chapter↗

The relative influence of geographic and environmental factors on rare plant translocation outcomes

Conservation translocations are an established method for reducing the extinction risk of plant species through intentional movement within or outside the indigenous range. Unsuitable environmental conditions at translocation recipient sites and a lack of understanding of species–environment relationships are often identified as critical barriers to translocation success. However, previous syntheses have drawn these inferences from analyses of qualitative feedback rather than quantitative environmental data. In this study, we use a data set of 235 translocations conducted in the US to understand the influences of geographic and environmental factors on three metrics of translocation success: population persistence, next-generation recruitment and next-generation maturity. We use random forest models to quantify the relative importance of geographic and environmental factors that characterize dissimilarity between source and recipient locations, the position of recipient sites relative to species' ranges and niche metrics derived from these ranges. We also compare the importance of these variables with more conventional predictors (e.g. founder population size). Our results indicate that geographic and environmental variables can be as insightful as conventional variables for predicting plant translocation outcomes. The climate suitability of recipient sites, estimated using species distribution models, was the strongest relative predictor of whether a population persisted, with populations situated in more suitable climates displaying greater persistence. Next-generation recruitment and maturity were best predicted by niche metrics; species in more biotically limiting environments, including tropical regions and soils with high relative nutrient retention, as well as species with the broadest precipitation niches, were the least likely to attain these next-generation benchmarks. Synthesis and applications . Our study is one of the first to quantify the important role of spatial and climatic factors in rare plant translocation outcomes. We provide a novel geographic and environmental perspective on outcomes in plant translocations and demonstrate opportunities to improve translocation success not only by adhering to established best practice guidelines but also by integrating spatial modelling approaches into planning and management processes.

Journal of Applied Ecology↗

Assessing biological effects from highway-runoff constituents

Increased emphasis on evaluation of nonpoint-source pollution has intensified the need for techniques that can be used to discern the toxicological effects of complex chemical mixtures. In response, the use of biological assessment techniques is receiving increased regulatory emphasis. When applied with documented habitat assessment and chemical analysis, these techniques can increase our understanding of the influence of environmental contaminants on the biological integrity and ecological function of aquatic communities. The contaminants of greatest potential concern in highway runoff are those that arise from highway construction, maintenance, and use. The major contaminants of interest are deicers; nutrients; metals; petroleum-related organic compounds, such as polycyclic aromatic hydrocarbons (PAHs), benzene, toluene, ethylbenzene, and xylene (BTEX), and methyl tert -butyl ether (MTBE); sediment washed off the road surface; and agricultural chemicals used in highway maintenance. Hundreds, if not thousands, of biological endpoints (measurable responses of living organisms) may be either directly or associatively affected by contaminant exposure. Measurable effects can occur throughout ecosystem processes across the wide range of biological complexity, ranging from responses at the biochemical level to the community level. The challenge to the environmental scientist is to develop an understanding of the relationship of effects at various levels of biological organization in order to determine whether a causal relationship exists between chemical exposure and substantial ecological impairment. This report provides a brief history of the evolution of biological assessment techniques, a description of the major classes of contaminants that are of particular interest in highway runoff, an overview of representative biological assessment techniques, and a discussion of data-quality considerations. Published reports with a focus on the effects of highway runoff on the local ecosystem were reviewed to provide information on (1) the suitability of the existing data for a quantitative national synthesis, (2) the methods available to study the effects of highway runoff on local ecosystems, and (3) the potential for adverse effects on the roadside environment and receiving waters. Although many biological studies have been done, the use of different methods and a general lack of sufficient documentation precludes a quantitative national synthesis on the basis of the existing data. The Federal Highway Administration, the U.S. Environmental Protection Agency, the U.S. Geological Survey, the Intergovernmental Task Force on Monitoring Water Quality, and the National Resources Conservation Service all have developed and documented methods for assessing the effects of contaminants on ecosystems in receiving waters. These published methods can be used to formulate a set of protocols to provide consistent information from highway-runoff studies. Review of the literature indicates (qualitatively) that highway runoff (even from highways with high traffic volume) may not usually be acutely toxic. Tissue analysis and community assessments, however, indicate effects from highway- runoff sediments near discharge points (even from sites near highways with relatively low traffic volumes). At many sites, elevated concentrations of highway-runoff constituents were measured in tissues of species associated with aquatic sediments. Community assessments also indicate decreases in the diversity and productivity of aquatic ecosystems at some sites receiving highway runoff. These results are not definitive, however, and depend on many site-specific criteria that were not sufficiently documented in most of the studies reviewed.

Open-File Report↗

Physical condition and stress levels during early development reflect feeding rates and predict pre- and post-fledging survival in a nearshore seabird

The effects of acute environmental stressors on reproduction in wildlife are often difficult to measure because of the labour and disturbance involved in collecting accurate reproductive data. Stress hormones represent a promising option for assessing the effects of environmental perturbations on altricial young; however, it is necessary first to establish how stress levels are affected by environmental conditions during development and whether elevated stress results in reduced survival and recruitment rates. In birds, the stress hormone corticosterone is deposited in feathers during the entire period of feather growth, making it an integrated measure of background stress levels during development. We tested the utility of feather corticosterone levels in 3- to 4-week-old nestling brown pelicans ( Pelecanus occidentalis ) for predicting survival rates at both the individual and colony levels. We also assessed the relationship of feather corticosterone to nestling body condition and rates of energy delivery to nestlings. Chicks with higher body condition and lower corticosterone levels were more likely to fledge and to be resighted after fledging, whereas those with lower body condition and higher corticosterone levels were less likely to fledge or be resighted after fledging. Feather corticosterone was also associated with intracolony differences in survival between ground and elevated nest sites. Colony-wide, mean feather corticosterone predicted nest productivity, chick survival and post-fledging dispersal more effectively than did body condition, although these relationships were strongest before fledglings dispersed away from the colony. Both reproductive success and nestling corticosterone were strongly related to nutritional conditions, particularly meal delivery rates. We conclude that feather corticosterone is a powerful predictor of reproductive success and could provide a useful metric for rapidly assessing the effects of changes in environmental conditions, provided pre-existing baseline variation is monitored and understood.

Gulf of Mexico↗

Merging integrated population models and individual-based models to project population dynamics of recolonizing species

Recolonizing species exhibit unique population dynamics, namely dispersal to and colonization of new areas, that have important implications for management. A resulting challenge is how to simultaneously model demographic and movement processes so that recolonizing species can be accurately projected over time and space. We introduce a framework for spatially explicit projection modeling that harnesses the rigorous parameter estimation made possible by an integrated population model (IPM) and the flexible movement modeling made possible by an individual-based model (IBM). Our framework has two components: [1] a Bayesian IPM-driven age- and state-structured population model that governs the population state process and estimation of demographic rates, and [2] an IBM-driven spatial model that allows for the projection of dispersal and habitat colonization. We applied this model framework to estimate current and project future dynamics of gray wolves ( Canis lupus ) in Washington State, USA. We used data from 74 telemetered wolves and yearly pup and pack counts to parameterize the model, and then projected statewide dynamics over 50 years. Mean population growth was 1.29 (95 % Bayesian Credible Interval = 1.26–1.33) during initial recolonization from 2009 to 2020 and decreased to 1.02 (95 % Prediction Interval = 0.98–1.04) in the projection period (2021–2070). Our results suggest that gray wolves have an ~100 % probability of colonizing the last of Washington State's three specified recovery regions by 2030, regardless of alternative assumptions about how dispersing wolves select new territories. Our spatially explicit projection model can be used to project the dynamics of any species for which spatial spread is an important driver of population dynamics.

Washington↗

Navigating the science-policy interface

As a wildlife population ecologist who wants to conduct useful science, I find the Endangered Species Act (ESA), like other federal wildlife statutes, an intriguing read. The topic is in my wheelhouse—fish, wildlife, and plants, with a focus at the population and species levels. There is an emphasis on science, in fact, the “best scientific and commercial data available.” And there are intriguing questions: what threats does a species face? What habitat would be critical for its survival? Could any federal actions put the species or critical habitat in greater peril? I am not alone in this attraction. Hundreds of scientists continue to consider the types of scientific analysis suggested by the ESA. The enthusiasm is palpable. If the first cursory read of the ESA is intriguing to me as a scientist, the second close read is tantalizing—I realize that something very attractive is just out of reach. I know how to estimate the probability of extinction, but I do not know what “in danger of extinction” means. I know how to evaluate the incremental change in status that might arise from some level of proposed take, but I do not know what “is not likely to jeopardize the continued existence” of a species means. The standards expressed in the statute are not stated in purely scientific terms. Thus, ESA decisions cannot be based solely on science, and require additional policy interpretation. Clarity about these policy interpretations—even awareness that they are needed—can be hard to find, leaving a gap between what I can provide as a scientist and what an ESA decision maker needs. This awareness of the interaction between science and policy is also occurring in the larger field of conservation science, where there has been an increasing recognition of a research-implementation gap, the need for actionable science, and the promise of translational ecology. All of these terms emphasize that science alone does not result in action; instead, action arises out of decisions that are informed both by science and by values. At the interface of science and policy, a scientist can deliver relevant knowledge, and a decision maker can explain the policy context in which that science is needed. As a scientist wanting to conduct useful science, I crave this two-way conversation. But how can this conversation be structured in a meaningful and appropriate way? In this chapter, I explore how decision analysis can be used to navigate the science-policy interface for ESA decisions. Decision analysis is a large, well-established field that studies how decisions are made and how they could be made, with explicit attention given to clarifying and separating the values-based and science-based elements of a decision; identifying the impediments that make a decision difficult; and providing tools to overcome those impediments. There have been concerted efforts to apply formal decision analysis to ESA decisions, but the practice is not yet widespread across both the U.S. Fish and Wildlife Service and the National Marine Fisheries Service (the Services). The chapter begins with an introduction to decision analysis and how it seeks to bridge the science-policy interface. In subsequent sections, I explore how a decision analyst might frame listing and reclassification decisions, recovery planning, section 7 consultation, budget allocations, and a few other ESA decisions, with an emphasis on two questions: for each type of decision, what policy clarifications does the decision maker need to make; and knowing the policy context, what type of scientific assessment is needed. In the final discussion, I identify common themes among the types of decisions, and offer thoughts on how decision analysis could be more widely used to integrate science into ESA decisions.

Book chapter↗

The Everglades Depth Estimation Network (EDEN) surface-water model, version 2

The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that generate daily water-level and water-depth data, and applications that compute derived hydrologic data across the freshwater part of the greater Everglades landscape. The U.S. Geological Survey Greater Everglades Priority Ecosystems Science provides support for EDEN in order for EDEN to provide quality-assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The EDEN surface-water model, version 2 (V2), interpolates water-level data from a network of 240 gages to generate gridded daily water-level surfaces for the freshwater domain of the Everglades. When these spatiotemporal continuous surfaces are combined with EDEN’s digital elevation model of ground surface, derived hydrologic data provide scientists and water managers working in the Everglades with data necessary to analyze ecological and biotic responses to hydrologic changes in the Everglades. Derived datasets include water depth, recession rates, days since last dry, water-surface slopes, and hydroperiod. The V2 model includes enhancements from the previous model (version 1; V1) to accommodate changes in the water-level gage network, adjustments to water-level data, improved understanding of the flow dynamics (particularly near canals), and installation of an elevation benchmark network. Enhancements to the V2 model included Expansion of the EDEN domain: The model domain was expanded to include a part of southern Big Cypress National Preserve and northwestern Everglades National Park upstream of the marsh mangrove wetlands, thus completing the coastal connection along the southwestern boundary of the model; and Development of subdomain models: To account for insufficient water-control structure gage data at some subbasin boundaries, subdomain models were developed for five subdomains, and the resulting water-level surfaces were merged to generate the final water-level surface. Model performance statistics show a general improvement in the V2 model as compared to the V1 model. Overall, the root mean squared error (RMSE) was reduced by 2.42 centimeters (cm) to 4.68 cm. In Water Conservation Area 3A North and Water Conservation Area 3B, the RMSE was reduced by 10.88 and 9.15 cm, respectively. In addition to evaluating model performance statistics, 2-cm water-level maps were generated and evaluated for irregular contours that would indicate a potential problem either with data input or water-level estimates. Three applications of the EDEN-modeled water surfaces and other EDEN datasets are presented in the report to show how scientists and resource managers are using EDEN datasets to analyze biological and ecological responses to hydrologic changes in the Everglades. The biological responses of two important Everglades species, alligators and wading birds, to changes in hydrology are described. The effects of hydrology on fire dynamics in the Everglades are also discussed.

Florida↗

Isolation by a hydroelectric dam induces minimal impacts on genetic diversity and population structure in six fish species

Reduced connectivity created by artificial barriers can influence the genetic integrity of isolated subpopulations by reducing local population sizes and altering patterns of gene flow. We investigated the genetic impacts of one such barrier, the Prairie du Sac dam, Wisconsin, USA, using microsatellite data from six fish species with varying life history traits sampled above and below the dam. Contrary to many past studies in other systems, we did not detect any significant differences in genetic diversity between populations found above and below the Prairie du Sac dam. Our results also revealed low genetic differentiation ( F ST = 0–0.008) between populations above and below the dam for all species. In fact, we found that more genetic variation was partitioned among sampling years than between above and below dam populations for all but one of the species. Results from coalescent simulations designed to model our study system indicated that the genetic impacts of the dam will likely be detectable approximately 40–60 generations after the dam was constructed, and that it is possible to largely mitigate these impacts with a fish passage strategy that facilitates a migration rate of ≥ 1% between above and below dam populations. In summary, our findings suggest the genetic impacts of dams can be relatively minimal on short time scales, and that fish passage strategies can significantly reduce genetic impacts if designed appropriately.

Wisconsin↗