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At least 919 records · Page 51Linked to original sources

Rigorously valuing the impact of projected coral reef degradation on coastal hazard risk in Florida

The degradation of coastal habitats, particularly coral reefs, raises risks by increasing the exposure of coastal communities to flooding hazards. In the United States, the physical protective services provided by coral reefs were recently assessed, in social and economic terms, with the annual protection provided by U.S. coral reefs off the coast of the State of Florida estimated to be more than 5,600 people and $675 million (2010 U.S. dollars). Degradation of coral reef ecosystems over the past several decades and during tropical storm events has caused regional-scale erosion of the shallow seafloor that serves as a protective barrier against coastal hazards along Southeast Florida, increasing risks to coastal populations. Here we combine engineering, ecologic, geospatial, social, and economic data and tools to provide a rigorous valuation of the increased hazard faced by Florida’s reef-fronted coastal communities because of the projected degradation of its adjacent coral reefs. We followed risk-based valuation approaches to map flood zones at 10-square-meter resolution along all 430 kilometers of Florida’s reef-lined shorelines for both the current and projected future coral reef conditions. We quantified the coastal flood risk increase caused by coral reef degradation using the latest information from the U.S. Census Bureau, Federal Emergency Management Agency, and Bureau of Economic Analysis for return-interval storm events. Using the damages associated with each storm probability, we also calculated the change in annual expected damages, a measure of the annual protection lost because of projected coral reef degradation. We found that degradation of the coral reefs off Florida increases future risks significantly. In particular, we estimated the protection lost by Florida’s coral reefs from projected coral reef degradation will result in: Increased flooding to more than 8.77 square kilometers (3.39 square miles) of land annually; Increased flooding affecting more than 7,300 people annually; Increased direct damages of more than $385.4 million to more than 1,400 buildings annually; and Increased indirect damages to more $438.1 million in economic activity owing to housing and business damage annually. Thus, the annual value of increased flood risk caused by the projected degradation of Florida’s coral reefs is more than 7,300 people and $823.6 million (2010 U.S. dollars). These data provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when degradation of Florida’s coral reefs will decrease critical coastal storm flood reduction benefits. These results help identify areas where reef management, recovery, and restoration could potentially help reduce the risk to, and increase the resiliency of, Florida’s coastal communities.

Florida↗

Assessing impacts of roads: application of a standard assessment protocol

Adaptive management of road networks depends on timely data that accurately reflect the impacts those systems are having on ecosystem processes and associated services. In the absence of reliable data, land managers are left with little more than observations and perceptions to support management decisions of road-associated disturbances. Roads can negatively impact the soil, hydrologic, plant, and animal processes on which virtually all ecosystem services depend. The Interpreting Indicators of Rangeland Health (IIRH) protocol is a qualitative method that has been demonstrated to be effective in characterizing impacts of roads. The goal of this study were to develop, describe, and test an approach for using IIRH to systematically evaluate road impacts across large, diverse arid and semiarid landscapes. We developed a stratified random sampling approach to plot selection based on ecological potential, road inventory data, and image interpretation of road impacts. The test application on a semiarid landscape in southern New Mexico, United States, demonstrates that the approach developed is sensitive to road impacts across a broad range of ecological sites but that not all the types of stratification were useful. Ecological site and road inventory strata accounted for significant variability in the functioning of ecological processes but stratification based on apparent impact did not. Analysis of the repeatability of IIRH applied to road plots indicates that the method is repeatable but consensus evaluations based on multiple observers should be used to minimize risk of bias. Landscape-scale analysis of impacts by roads of contrasting designs (maintained dirt or gravel roads vs. non- or infrequently maintained roads) suggests that future travel management plans for the study area should consider concentrating traffic on fewer roads that are well designed and maintained. Application of the approach by land managers will likely provide important insights into minimizing impacts of road networks on key ecosystem services.

Rangeland Ecology and Management↗

Geologic information for aggregate resource planning

Construction and maintenance of the infrastructure is dependent on such raw materials as aggregate (crushed stone, sand, and gravel). Despite this dependence, urban expansion often works to the detriment of the production of those essential raw materials. The failure to plan for the protection and extraction of aggregate resources often results in increased consumer cost, environmental damage, and an adversarial relation between the aggregate industry and the community. As an area grows, the demand for aggregate resources increases, and industries that produce these materials are established. Aggregate is a low-cost commodity, and to keep hauling costs at a minimum, the operations are located as close to the market as possible. As metropolitan areas grow, they encroach upon established aggregate operations. New residents in the vicinity of pits and quarries object to the noise, dust, and truck traffic associated with the aggregate operation. Pressure is applied to the local government to limit operation hours and truck traffic. In addition to encroaching on established aggregate operations, urban growth commonly covers unmined aggregate resources. Frequently urban growth occurs without any consideration of the resource or an analysis of the impact of its loss. The old idea that aggregate resources can be found anywhere is false. New aggregate operations may have to be located long distances from the markets. The additional expense of the longer transport of resources must be passed on to consumers in the community. In many instances, the new deposit is of inferior quality compared with the original source, yet it is used to avoid the expense of importing high-quality material from a more-distant source. Some governmental, including city, provincial or state, and national, agencies, have enacted regulations to help maintain access to prime aggregate resources. Although regulations have met with variable success, some policy or regulation to protect aggregate resources is worth consideration. A basic requirement of any aggregate resource policy or regulation is the knowledge of the geographic distribution, volumes, and quality of aggregate resources. This knowledge commonly is obtained through geologic mapping and characterization of aggregate resources. Geographic Information Systems (GIS) and Decision Support Systems (DSS) provide excellent tools to help present and evaluate the information in a manner that is understandable by public decisionmakers.

Book chapter↗

Optimizing release strategies: A stepping-stone approach to reintroduction

Evaluation of alternative management strategies enables informed decisions to accelerate species recovery. For reintroductions, post-release survival to reproductive age is a key parameter influencing population growth. Here we trial a ‘stepping-stone’ method to maximize the success of captive-bred animals when the availability of more suitable wild-born release candidates is limited. Our approach makes use of relatively safe and established wild populations to prepare captive-bred individuals for eventual translocation to a final release destination, thus building resilience through establishment of multiple populations over time. We developed a novel multievent model integrating encounter history and biotelemetry data to evaluate reintroduction strategies for the critically endangered Vancouver Island marmot (Marmota vancouverensis). We compared post-release survival of 176 individuals (52 wild-born, 47 captive-bred marmots released directly to destinations, and 77 captive-bred marmots released with a stepping-stone approach). Survival estimates to prime breeding-age (PBA), were then used to quantify expected success of potential release strategies. Our analysis indicates that post-release survival varies by source population and release method, as well as age, season, year, and years since release. Conditional on an objective of maximizing survival to PBA, our results suggest that using wild-born marmots for translocations as often as possible, and stepping-stone captive-bred marmots prior to final release, will result in the best outcomes. There was a 0.86 probability that survival to PBA was greater for captive-bred marmots released as yearlings using a stepping-stone approach (survival to PBA mode = 0.13, 95% CRI = 0.05-0.30) than for captive-bred animals that were directly released to destination sites as one-year-olds (survival to PBA mode = 0.04, 95% CRI = 0.01-0.24). Consequently, the stepping-stone approach yields much higher population establishment or growth potential than previous release strategies that used captive-bred marmots. Optimizing the combination of release candidates, sites, and timing can thereby increase the effectiveness of reintroductions.

British Columbia↗

Modeling, mapping, and measuring the risk of freshwater invasive species across Alaska

Freshwater ecosystems of the Alaskan Arctic and Subarctic provide resources that are culturally, ecologically, and economically invaluable. Presently, these regions are relatively free of the impacts from invasive species compared to southern latitudes. To date, there have been relatively few verified introductions of aquatic invasive species (AIS) to freshwater ecosystems in Alaska. The expanding list and distribution of AIS has led to significant negative ecological and economic impacts (e.g., waterweed Elodea nuttalli ; E. canadensis and northern pike Esox Lucius introduced outside its native range in Alaska). Escalating human activity across Alaskan lands and waters, coupled with rapidly shifting environmental conditions, increases the potential for new species introductions and subsequent establishment. Creating a proactive framework for well-informed decision-making and action can improve the effectiveness of prevention efforts and bolster decision support tools that help resource managers direct limited resources. Prioritizing AIS that may be introduced and become established, as well as the locations at highest risk of invasion, is foundational to building a proactive invasive species management framework in Alaska. This project sought to identify and prioritize AIS known to be invasive in the contiguous United States, evaluate current and future habitat suitability for AIS in Alaska, and assess potential for AIS to be transported to habitats across Alaska, utilizing similar assessment methods as implemented for Bering Sea marine invasive species and non-native plants in Alaska. To accomplish this goal, the objectives of the project were to: 1) develop a formal ranked list of potential AIS to freshwater systems of Alaska; 2) assess the level of establishment risk for potential AIS by developing habitat suitability models for waterbodies across Alaska; and 3), identify potential pathways and specific vectors for high-risk AIS to invade Alaska and develop a framework for how vector analysis will be completed to understand transport risk. Overall, our goal is horizon scanning which is defined by Roy et al. (2019) as “a systematic examination of potential threats and opportunities, within a given context, and likely future developments, which are at the margin of current thinking and planning.” The scans include pathway analyses and risk screening of species present at pathway origin points, with a focus on identifying species at high risk of being introduced, becoming established, spreading, and causing harm. We refined a list of 28 AIS from a list of hundreds based on characterizations of species’ invasiveness and species’ proximity to Alaska (USGS 2020; GBIF 2022). Next, we evaluated the relative invasiveness of individual species to create an initial AIS ranking. We sought to characterize habitat suitability of AIS by selecting variables that were continental in scale, covering North America to include Alaska as well as the lower 48 states comparing natural discharge, sub-basin average terrain slope (degrees), average silt fraction, average organic carbon, lithological class, and human footprint in sub-basin in 2009. We estimated AIS habitat suitability across the entire state of Alaska using the physiological tolerances of the AIS (Appendix 2). We also evaluated pathways and vectors for the introduction of AIS (Appendix 2). Many pathways and vectors considered did not meet the criteria for Alaska or freshwater systems. Of the 28 ranked species that we categorized as very high, high, and moderate levels of invasiveness; all three risk groups included fish and mollusks (Appendix 2). One commonality of the very high-invasiveness-ranked species was the availability of Ecological Risk Screening Summary documents (USFWS, 2022) produced by U.S. Fish and Wildlife Service (USFWS), except for the goldfish ( Carassius auratus ) and the New Zealand mudsnail ( Potamopyrgus antipodarum ). The Ecological Risk Screening Summary is now available for New Zealand mudsnails. In general, fish species often ranked very high or high in invasiveness and included sportfish and aquarium fish, suggesting the importance of pathways such as aquarium trade, fishing industry, intentional (but illegal) introductions of sportfishes and aquarium fishes for establishment. The technique we used for habitat suitability models necessitated aquatic environmental datasets that were continental in scale, which was often interpolated from very coarse resolution source data layers, particularly in Alaska. Better spatial data representing aquatic environments would likely improve this approach. While the lack of introductions in Alaska and nearby provinces and states is encouraging, the lack of occurrence data for the focal species also created complications for habitat suitability modeling. Despite the challenges, the habitat suitability models indicated limited suitability for warmwater species while some species, such as Brook trout (S alvelinus fontinalis ), have high habitat suitability across Alaska no matter what threshold approach is taken. Some environmental predictors were more important than others. Specifically, the most important predictor variable, ‘frost free days,’ was critical for 15 out of 28 species as expected due to harsh winter conditions in Arctic and Subarctic regions. The second most important predictor was ‘subbasin land surface runoff’, a variable that indicates the amount of discharge and runoff, while the third most important predictor was ‘snow cover’ another indication of winter conditions. Overall, the ability to understand the effect of future climate scenarios on the establishment of AIS was challenging. A detailed dataset of freshwater temperatures and water chemistry (e.g., pH, calcium) would greatly improve the ability to predict invasiveness of freshwater species to Alaska’s ecosystems on a regional basis. Future studies may benefit from a more focused geographic scope examining a group of subbasins or a regional basin rather than the entire state. These drainages could be selected based upon the mostly likely locations of introduction pathways. The two most prevalent pathway risks for AIS are in-state transfer and stowaways/contaminants. Although there are examples of introductions from other pathways, the risk is somewhat mitigated by Alaska’s climate and regulations. However, variable application of protocols for inspection and cleaning of fishing gear, watercraft, and other similar items while traveling into Alaska as well as transferring from waterbody to waterbody within the state creates a substantial risk in introducing invasive species. We plot cumulative invasive vulnerability for all subbasins and for the top 10% of subbasins (Appendix 3).

Alaska↗

Towards globally customizable ecosystem service models

Scientists, stakeholders and decision makers face trade-offs between adopting simple or complex approaches when modeling ecosystem services (ES). Complex approaches may be time- and data-intensive, making them more challenging to implement and difficult to scale, but can produce more accurate and locally specific results. In contrast, simple approaches allow for faster assessments but may sacrifice accuracy and credibility. The ARtificial Intelligence for Ecosystem Services (ARIES) modeling platform has endeavored to provide a spectrum of simple to complex ES models that are readily accessible to a broad range of users. In this paper, we describe a series of five “Tier 1” ES models that users can run anywhere in the world with no user input, while offering the option to easily customize models with context-specific data and parameters. This approach enables rapid ES quantification, as models are automatically adapted to the application context. We provide examples of customized ES assessments at three locations on different continents and demonstrate the use of ARIES' spatial multi-criteria analysis module, which enables spatial prioritization of ES for different beneficiary groups. The models described here use publicly available global- and continental-scale data as defaults. Advanced users can modify data input requirements, model parameters or entire model structures to capitalize on high-resolution data and context-specific model formulations. Data and methods contributed by the research community become part of a growing knowledge base, enabling faster and better ES assessment for users worldwide. By engaging with the ES modeling community to further develop and customize these models based on user needs, spatiotemporal contexts, and scale(s) of analysis, we aim to cover the full arc from simple to complex assessments, minimizing the additional cost to the user when increased complexity and accuracy are needed.

Science of the Total Environment↗

Water-quality characteristics for selected sites within the Milwaukee Metropolitan Sewerage District planning area, Wisconsin, February 2004-September 2005

The Milwaukee Metropolitan Sewerage District (MMSD) Corridor Study is a three-phase project designed to improve the understanding of water resources in the MMSD planning area to assist managers and policy makers in their decisions. Phase I of the Study involved the compilation of existing data from multiple agencies into a single database. These data were analyzed to identify spatial, temporal, and technological gaps in the planning area, and were used to develop Phase II of the Study. Phase II, the subject of this report, involved an intensive data-collection effort by the U.S. Geological Survey (USGS) in cooperation with MMSD (from February, 2004, through September, 2005). This phase addressed the data gaps identified in Phase I and completed a baseline assessment of water quality for selected stream and harbor sites in the MMSD planning area. This baseline assessment included evaluations of surface-water chemistry and microbial concentrations in the streams and harbor sites; additionally, stream sites were evaluated for discharge, sediment chemistry, fish-tissue chemistry, habitat, and the quality of biological communities (including fish, macroinvertebrates, and algae). In all, data were collected at 15 stream and 6 harbor sites within the MMSD planning area, including manual sampling and analysis for more than 220 water-quality properties and constituents at all 21 sites, stream-discharge data for 14 stream sites, and automated water-quality sampling at 4 stream sites. A bioassessment during autumn 2004 included collection of biologic-community data and stream-habitat data at wadeable streams. Quartiles of Phase II aggregate bioassessment rankings were used to divide the 14 wadeable stream sites into four groups to investigate relations between bioassessment data and site characteristic and water-quality data. Quartile numbers reflect relative water quality: quartile 1 contained sites where the bioassessment data indicated the least-degraded water quality among those sampled, and quartile 4 contained sites that indicated the most-degraded water quality. Quartiles contained the following stream sites: Quartile 1: Milwaukee River near Cedarburg, Milwaukee River at Milwaukee, Jewel Creek, and Menomonee River at Menomonee Falls; Quartile 2: Willow Creek, Root River near Franklin, and Root River at Grange Avenue; Quartile 3: Menomonee River at Wauwatosa, Oak Creek, and Little Menomonee River; and Quartile 4: Honey Creek, Underwood Creek, Lincoln Creek, and Kinnickinnic River. Site characteristics (in this case, drainage area and land use) and selected water-quality data were summarized based on the four bioassessment quartiles to determine if there were relations with the aggregate bioassessment rankings. In general, sites having the largest drainage basins with the lowest proportion of urban land use were in quartile 1, and the smallest drainage basins with the highest proportion of urban land use were in quartile 4. Major ions, indicator organisms, and wastewater compounds generally had the lowest overall results in quartile 1 and highest overall results in quartile 4, with intermediate results in quartiles 2 and 3. Results for other constituent types (nutrients, mercury, pathogenic organisms, and bed sediment) were mixed, with results for some constituents decreasing from quartile 1 to quartile 4. Where sufficient Phase I data were available, summary statistics (including medians) for chemical and biological data were calculated, allowing some comparisons to be made between Phase I and Phase II data. Comparisons between Phase I and Phase II results indicated a variety of changes with respect to water quality. Concentrations of chloride, nitrate, chlorophyll a, total phosphorus in water; arsenic in bed sediment; and fish Index of Biotic Integrity ratings generally indicated declines in water quality. However, concentrations of total nitrogen, suspended sediment, and fecal coliform in water; some trace eleme

Wisconsin↗

Characteristics of mangrove swamps managed for mosquito control in eastern Florida, USA

Manipulations of the vegetation and hydrology of wetlands for mosquito control are common worldwide, but these modifications may affect vital ecosystem processes. To control mosquitoes in mangrove swamps in eastern Florida, managers have used rotational impoundment management (RIM) as an alternative to the worldwide practice of mosquito ditching. Levees surround RIM swamps, and water is pumped into the impoundment during the summer, a season when natural swamps have low water levels. In the New World, these mosquito-managed swamps resemble the mixed basin type of mangrove swamp (based on PCA analysis). An assessment was made of RIM, natural (control), and breached-RIM (restored) swamps in eastern Florida to compare their structural complexities, soil development, and resistance to invasion. Regarding structural complexity, dominant species composition differed between these swamps; the red mangrove Rhizophora mangle occurred at a higher relative density in RIM and breached-RIM swamps, and the black mangrove Avicennia germinans had a higher relative density in natural swamps. Tree density and canopy cover were higher and tree height lower in RIM swamps than in natural and breached-RIM swamps. Soil organic matter in RIM swamps was twice that in natural or breached-RIM swamps. RIM swamps had a lower resistance to invasion by the Brazilian pepper tree Schinus terebinthifolius , which is likely attributable to the lower porewater salinity in RIM swamps. These characteristics may reflect differences in important ecosystem processes (primary production, trophic structure, nutrient cycling, decomposition). Comparative assessments of managed wetlands are vital for land managers, so that they can make informed decisions compatible with conservation objectives.

Florida↗

Assessing cropland area in west Africa for agricultural yield analysis

Accurate estimates of cultivated area and crop yield are critical to our understanding of agricultural production and food security, particularly for semi-arid regions like the Sahel of West Africa, where crop production is mainly rain-fed and food security is closely correlated with the inter-annual variations in rainfall. Several global and regional land cover products, based on satellite remotely-sensed data, provide estimates of the agricultural land use intensity, but the initial comparisons indicate considerable differences among them, relating to differences in the satellite data quality, classification approaches, and spatial and temporal resolutions. Here, we quantify the accuracy of available cropland products across Sahelian West Africa using an independent, high-resolution, visually interpreted sample dataset that classifies all points across West Africa using a 2-km sample grid (~500,000 points for the study area). We estimate the “quantity” and “allocation” disagreements for the cropland class of eight land cover products in five Western Sahel countries (Burkina Faso, Mali, Mauritania, Niger, and Senegal). The results confirm that coarse spatial resolution (300 m, 500 m, and 1000 m) land cover products have higher disagreements in mapping the fragmented agricultural landscape of the Western Sahel. Earlier products (e.g., GLC2000) are less accurate than recent products (e.g., ESA CCI 2013, MODIS 2013 and GlobCover 2009). We also show that two of the finer spatial resolution maps (GFSAD30, and GlobeLand30) using advanced classification approaches (random forest, decision trees, and pixel-object combined) are currently the best available products for cropland identification. However, none of the eight land cover databases examined is consistent in reaching the targeted 75% accuracy threshold in the five Sahelian countries. The majority of currently available land cover products overestimate cultivated areas by an average of 170% relative to the cropland area in the reference data.

Remote Sensing↗

Protocol for Monitoring Fish Assemblages in Pacific Northwest National Parks

Rivers and streams that drain from Olympic, Mount Rainier, and North Cascades National Parks are among the most protected corridors in the lower 48 States, and represent some of the largest tracts of contiguous, undisturbed habitat throughout the range of several key fish species of the Pacific Northwest. These watersheds are of high regional importance as freshwater habitat sanctuaries for native fish, where habitat conditions are characterized as having little to no disturbance from development, channelization, impervious surfaces, roads, diversions, or hydroelectric projects. Fishery resources are of high ecological and cultural importance in Pacific Northwest National Parks, and significantly contribute to economically important recreational, commercial, and tribal fisheries. This protocol describes procedures to monitor trends in fish assemblages, fish abundance, and water temperature in eight rivers and five wadeable streams in Olympic National Park during summer months, and is based on 4 years of field testing. Fish assemblages link freshwater, marine, and terrestrial ecosystems. They also serve as focal resources of national parks and are excellent indicators of ecological conditions of rivers and streams. Despite the vital importance of native anadromous and resident fish populations, there is no existing monitoring program for fish assemblages in the North Coast and Cascades Network. Specific monitoring objectives of this protocol are to determine seasonal and annual trends in: (1) fish species composition, (2) timing of migration of adult fish, (3) relative abundance, (4) age and size structure, (5) extent of non-native and hatchery fish, and (6) water temperature. To detect seasonal and annual trends in fish assemblages in reference sites, we rely on repeated and consistent annual sampling at each monitoring site. The general rationale for the repeated sampling of reference sites is to ensure that we account for the high interannual variability in fish movements and abundances in rivers. One underlying assumption is that the monitoring program is designed in perpetuity, and consequently our capability to detect trends substantially increases with time. The protocol describes sampling designs, methods, training procedures, safety considerations, data management, data analysis, and reporting. The allocation of sampling effort represents a balance between ecological considerations, a sound monitoring approach, and practical limitations caused by logistical constraints and a limited annual budget of $55,000. The widespread declines of native fish species in western North America highlights the importance and urgency of understanding trends in fish assemblages from undisturbed habitats. Seasonal and annual trends in fish assemblages will provide insights at the individual, population, and assemblage level. This protocol will allow managers to detect increases and decreases in abundance of priority management species, and occurrence of non-native, hatchery, and federally listed fish. The detection of trends in fish assemblages will allow for specific management actions that may include: implementation of more appropriate fishing regulations, evaluation of existing hatchery releases, control of non-native fish species, and prioritization of habitat restoration projects. Dissemination and communication of scientific findings on North Coast and Cascades Network fish assemblages will be a core product of this protocol, which will have much relevance to decision makers, park visitors, researchers, and educators.

Techniques and Methods↗

A tool for prioritizing gravel augmentation reaches for sediment starved rivers

Gravel augmentation is a widely used restoration technique used to improve habitat below dams, including salmonids spawning habitat. However, gravel augmentation can be cost-prohibitive, and it is often unclear which stream segments have the highest potential to benefit spawning salmonids. A tool to help prioritize reaches for gravel restoration could aid managers in making good decisions. To address this need, we convened a group of fishery managers to create Intrinsic Potential (IP) habitat models. We used stream attributes related to salmonid spawning habitat: elevation, width, and gradient from the synthetic stream channel dataset NetMap. We then used the IP models to develop an easy-to-use and flexible tool for identifying high spring-run Chinook Salmon ( Oncorhynchus tshawytscha ) IP along ~100 m reaches based on a conceptual model developed by the fishery managers. The tool allows for the inclusion of winter steelhead ( O. mykiss ) IP spawning habitat and allows users to incorporate mean August stream temperature maxima under recent conditions and projected under future climate change, land ownership (public or private or both), reach access distance, distance to and type of gravel sources, and relative gravel movement potential. We explore the prioritization tool with three demonstration strategies for the Upper Rogue River basin, Oregon, USA: (1) Spring Chinook Salmon Strategy, (2) Co-occurrence with winter steelhead Strategy, and (3) Climate Change Strategy. Our analysis demonstrates that altering management priorities directly influences which stream reaches are identified for gravel augmentation. In the three strategies we compared, a small number of current conservation reaches located downstream of spring Chinook Salmon spawning were identified using the tool. In addition, we identified a small number of reaches with no conservation strategy for winter steelhead spawning that meet prioritization criteria. Furthermore, under a climate change scenario, we highlight how new gravel source permitting could expand the set of viable augmentation reaches. The tool is publicly available on GitHub.

Oregon↗

State-and-transition models: Conceptual versus simulation perspectives, usefulness and breadth of use, and land management applications

State-and-Transition Simulation Modeling (STSM) is a quantitative analysis method that can consolidate a wide array of resource management issues under a “what-if” scenario exercise. STSM can be seen as an ensemble of models, such as climate models, ecological models, and economic models that incorporate human dimensions and management options. This chapter presents STSM as a tool to help synthesize information on social–ecological systems and to investigate some of the management issues associated with exotic annual Bromus species, which have been described elsewhere in this book. Definitions, terminology, and perspectives on conceptual and computer-simulated stochastic state-and-transition models are given first, followed by a brief review of past STSM studies relevant to the management of Bromus species. A detailed case study illustrates the usefulness of STSM for land management. As a whole, this chapter is intended to demonstrate how STSM can help both managers and scientists: (a) determine efficient resource allocation for monitoring nonnative grasses; (b) evaluate sources of uncertainty in model simulation results involving expert opinion, and their consequences for management decisions; and (c) provide insight into the consequences of predicted local climate change effects on ecological systems invaded by exotic annual Bromus species.

Book chapter↗

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

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

California↗

Reference intervals and physiologic alterations in hematologic and biochemical values of free-ranging desert tortoises in the Mojave Desert

Desert tortoise ( Gopherus agassizii ) populations have experienced precipitous declines resulting from the cumulative impact of habitat loss, and human and disease-related mortality. Evaluation of hematologic and biochemical responses of desert tortoises to physiologic and environmental factors can facilitate the assessment of stress and disease in tortoises and contribute to management decisions and population recovery. The goal of this study was to obtain and analyze clinical laboratory data from free-ranging desert tortoises at three sites in the Mojave Desert (California, USA) between October 1990 and October 1995, to establish reference intervals, and to develop guidelines for the interpretation of laboratory data under a variety of environmental and physiologic conditions. Body weight, carapace length, and venous blood samples for a complete blood count and clinical chemistry profile were obtained from 98 clinically healthy adult desert tortoises of both sexes at the Desert Tortoise Research Natural area (western Mojave), Goffs (eastern Mojave) and Ivanpah Valley (northeastern Mojave). Samples were obtained four times per year, in winter (February/March), spring (May/June), summer (July/August), and fall (October). Years of near-, above- and below-average rainfall were represented in the 5 yr period. Minimum, maximum and median values, and central 95 percentiles were used as reference intervals and measures of central tendency for tortoises at each site and/or season. Data were analyzed using repeated measures analysis of variance for significant ( P < 0.01) variation on the basis of sex, site, season, and interactions between these variables. Significant sex differences were observed for packed cell volume, hemoglobin concentration, aspartate transaminase activity, and cholesterol, triglyceride, calcium, and phosphorus concentrations. Marked seasonal variation was observed in most parameters in conjunction with reproductive cycle, hibernation, or seasonal rainfall. Year-to-year differences and long-term alterations primarily reflected winter rainfall amounts. Site differences were minimal, and largely reflected geographic differences in precipitation patterns, such that results from these studies can be applied to other tortoise populations in environments with known rainfall and forage availability patterns.

Journal of Wildlife Diseases↗

Analysis of groundwater response to tidal fluctuations, Operable Unit 1, Naval Base Kitsap, Keyport, Washington

Chlorinated volatile organic compounds have affected groundwater beneath a former 9-acre landfill at Operable Unit 1 (OU 1) of Naval Base Kitsap (NBK) Keyport, in Keyport, Washington. The landfill was the primary disposal area for domestic and industrial waste generated by NBK Keyport from the 1930s through 1973. Naval Facilities Engineering Command Northwest, in conjunction with the Environmental Protection Agency, Washington State Department of Ecology, and the Suquamish Tribe, is charged with collecting necessary data to monitor the contamination left in place and to ensure that the site does not pose a risk to human health or the environment. To support these efforts, refined information was collected on how groundwater levels throughout OU 1 respond to tidal fluctuations at this nearshore site adjacent to Liberty Bay, an inlet of Puget Sound. The information was analyzed to determine the optimal times during the semidiurnal and the neap-spring tidal cycles to sample groundwater for contaminants associated with fresh groundwater originating from OU 1. The optimal times for sampling are presumed to be when fresh groundwater flowing seaward is least impeded by elevated tides, and those times are related to predicted tide levels by tidal lags, the durations between low tides, and corresponding low groundwater levels. Discrete groundwater-specific conductance data also were collected to determine if a seawater/freshwater interface was present at any of the monitoring wells, and to inform decisions on the depth at which groundwater should be sampled in existing wells. Groundwater and surface-water levels were monitored at 19 monitoring wells and five adjacent surface-water sites. Specific conductance was monitored in each surface-water site. All time-series data parameters were collected every 15 minutes during a 4-week duration to measure how nearshore groundwater responds to tidal forcing. Time-series data were collected from July 12, 2018, to August 8, 2018, a period that included neap and spring tides. Vertical water-quality profiles were measured once in the screened interval of nine selected monitoring wells. The profiles included measurements at the top, middle, and bottom of each saturated screen interval. Tidal lag times were determined relative to tidal levels in Liberty Bay (rather than in the more nearby Tide Flats) because the predicted tides for the Poulsbo, Washington Station (National Oceanic and Atmospheric Administration [NOAA] Station 9445719) that are used to schedule groundwater sampling represent open-water conditions in the area; a sill that separates Dogfish Bay from the Tide Flats clearly affects the timing and magnitude of low-low tides in the Tide Flats. Calculated tidal lag times were divided into three general groups: (1) wells where groundwater responded to tidal level changes immediately, (2) wells where groundwater responded to tidal level changes within about 2–5 hours, and (3) wells where groundwater had minimal response to tidal level changes. Groundwater levels in the middle group of wells primarily responded in concert with tidal level changes in the Tide Flats rather than tidal level changes in Liberty Bay. An intended sampling depth refinement based on an assessment of transient seawater intrusion was not completed because of a failure to collect specific-conductance time-series data in select wells. Instead, discrete specific-conductance data from this and prior studies were evaluated to determine that the midpoint of well screens in OU 1 wells can be assumed to be a reasonably representative of undiluted groundwater. When sampling during spring (rather than neap) tides (as has generally been the standard practice at OU 1), the optimal time to sample the monitoring wells influenced by tides would be to add the tidal lags presented in this report to the time of the predicted low-low tide for Liberty Bay as measured at NOAA Station 9445719 at Poulsbo, Washington. Sampling schedules for the six wells where groundwater levels were only minimally influenced by tide changes should not be constrained by tidal conditions.

Washington↗

GT-Seq panel development for species identification and parentage analysis of closely related hybridising Scaphirhynchus sturgeons

Hatchery supplementation is vital for conserving dwindling fish populations. Effective augmentation requires distinguishing hatchery-origin from wild individuals and accurately identifying species, particularly in systems where closely related species coexist. Genetic monitoring is key to quantifying genetic differences, but conventional markers do not distinguish hybrids, especially backcrosses. Misidentifying hybrids in hatchery programs compromises wild gene pools because hatchery broodstock contributes to numerous offspring being released into the wild. Here, we present a workflow for developing and evaluating the Genotyping-in-Thousands by sequencing (GT-seq) single nucleotide polymorphism (SNP) panel for North American river sturgeons ( Scaphirhynchus spp.). This panel is designed to detect complex hybrid classes and to determine parent-offspring relationships. Our species identification panel (S-loci) contains 155 SNPs selected for high genetic differentiation (F ST ) between Pallid Sturgeon ( S. albus ) and Shovelnose Sturgeon ( S. platorynchus ), and the parentage assignment panel (P-loci) includes 112 SNPs with high heterozygosity within Pallid Sturgeon. Simulation analyses demonstrated that our GT-seq S-loci panel reliably classifies pure species, F1, F2 and backcross hybrids, even with up to 70% missing data. The P-loci panel achieves high-confidence parentage assignment with ≥ 80% typed loci, with performance influenced by the proportion of sampled parents. Overall, the novel Scaphirhynchus GT-seq panel developed in this study represents a robust and efficient tool for detecting hybridisation, assigning parentage and providing critical information for management decisions in ongoing Pallid Sturgeon conservation.

lower Mississippi River, Missouri River↗

Climate-induced shifts in grassland bird nesting phenology have implications for grassland management

Grasslands are among the most impacted ecosystems globally. In the midcontinent of North America, a > 80% loss of grasslands has made their conservation a major priority for resource managers. Grassland ecosystems evolved under periodic disturbances; consequently, grassland management often involves regular actions such as grazing, haying, or burning to maintain ecosystem integrity. The timing of such practices has direct implications on grassland ecology, agricultural economics, and survival and fecundity of grassland nesting birds (hereafter grassland birds). We conducted a meta-analysis on the nesting phenology of grassland birds throughout North America, focusing on nest-survival literature. We constructed a well-fitting model to predict median date of expected nest departure (hereafter fledge date) for grassland birds across the midcontinent. Predictions from our model demonstrate considerable spatial variation in median nesting phenology that is predictable using a spatially explicit spring phenology index. Median fledge dates were 8 or 13 days earlier in years of extreme weather conditions (dry or wet, respectively) than in years of average conditions. Species that generally nest in taller vegetation tended to have later median nest phenologies than those using shorter vegetation. Our results incorporate the most rigorous information available in the literature on nesting phenology of 36 grassland bird species and improve information available to managers about nesting phenology of grassland birds in the midcontinent of North America. Our predictions approximate the day when one-half of the nesting efforts would be complete for a given area within the midcontinent grasslands and can inform management and conservation decisions about the timing of management actions in grassland ecosystems.

Global Ecology and Conservation↗

Machine learning for predicting soil classes in three semi-arid landscapes

Mapping the spatial distribution of soil taxonomic classes is important for informing soil use and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial distribution of soil taxonomic classes. Key components of DSM are the method and the set of environmental covariates used to predict soil classes. Machine learning is a general term for a broad set of statistical modeling techniques. Many different machine learning models have been applied in the literature and there are different approaches for selecting covariates for DSM. However, there is little guidance as to which, if any, machine learning model and covariate set might be optimal for predicting soil classes across different landscapes. Our objective was to compare multiple machine learning models and covariate sets for predicting soil taxonomic classes at three geographically distinct areas in the semi-arid western United States of America (southern New Mexico, southwestern Utah, and northeastern Wyoming). All three areas were the focus of digital soil mapping studies. Sampling sites at each study area were selected using conditioned Latin hypercube sampling (cLHS). We compared models that had been used in other DSM studies, including clustering algorithms, discriminant analysis, multinomial logistic regression, neural networks, tree based methods, and support vector machine classifiers. Tested machine learning models were divided into three groups based on model complexity: simple, moderate, and complex. We also compared environmental covariates derived from digital elevation models and Landsat imagery that were divided into three different sets: 1) covariates selected a priori by soil scientists familiar with each area and used as input into cLHS, 2) the covariates in set 1 plus 113 additional covariates, and 3) covariates selected using recursive feature elimination. Overall, complex models were consistently more accurate than simple or moderately complex models. Random forests (RF) using covariates selected via recursive feature elimination was consistently the most accurate, or was among the most accurate, classifiers between study areas and between covariate sets within each study area. We recommend that for soil taxonomic class prediction, complex models and covariates selected by recursive feature elimination be used. Overall classification accuracy in each study area was largely dependent upon the number of soil taxonomic classes and the frequency distribution of pedon observations between taxonomic classes. Individual subgroup class accuracy was generally dependent upon the number of soil pedon observations in each taxonomic class. The number of soil classes is related to the inherent variability of a given area. The imbalance of soil pedon observations between classes is likely related to cLHS. Imbalanced frequency distributions of soil pedon observations between classes must be addressed to improve model accuracy. Solutions include increasing the number of soil pedon observations in classes with few observations or decreasing the number of classes. Spatial predictions using the most accurate models generally agree with expected soil–landscape relationships. Spatial prediction uncertainty was lowest in areas of relatively low relief for each study area.

New Mexico, Utah, Wyoming↗