Shorebird populations are declining globally but it generally remains unclear how those declines translate to changes at the regional scale. We conducted the first longitudinal surveys of breeding shorebirds in Alaska under the Program for Regional and International Shorebird Monitoring (PRISM), resurveying the Coastal Plain (1002 Area) of the Arctic National Wildlife Refuge (NWR) in 2019 and 2022 to compare with initial surveys conducted in 2002 and 2004. Our goals were to (1) estimate contemporary population sizes of breeding shorebirds across this 6,249 km(2) area, and (2) assess population trends for the species detected in both survey periods. We estimated population sizes for 16 species, with a combined total of 135,178 (95% CI: 113,532-156,824) in 2019 and 2022-a decline of approximately 17% (90% CI: -34% to +3%) from 2002 and 2004 when the same survey methods were used. Four species showed a statistically significant decrease (alpha = 0.10): Calidris alpina arcticola (Dunlin), Limnodromus scolopaceus (Long-billed Dowitcher), Phalaropus lobatus (Red-necked Phalarope), and P. fulicarius (Red Phalarope). Only C. melanotos (Pectoral Sandpiper) showed a significant increase. Overall, 5 of 10 species-and all species combined-had a > 90% probability of decline. Population changes for the polygamous species (i.e., Phalaropus sp. and C. melanotos), which show irruptive breeding and low breeding site fidelity, may reflect temporary immigration or emigration driven by annual environmental variation, rather than true population change. Nevertheless, the overall pattern of declines aligns with migration surveys outside the Arctic. These findings highlight the vulnerability of Arctic-breeding shorebirds to threats throughout their annual cycles and underscore the potential for sustained long-term monitoring in this rapidly changing region to inform effective, flyway-scale conservation strategies across the Western Hemisphere.

Red Knots (Calidris canutus rufa) rely on Atlantic horseshoe crab (Limulus polyphemus) eggs in the Delaware Bay to refuel during northward migration. Intensive harvest of horseshoe crabs in the 1990s contributed to declines in Red Knot numbers. In 2013, the Atlantic States Marine Fisheries Commission adopted an Adaptive Resource Management (ARM) framework to balance sustainable horseshoe crab harvest with ecosystem integrity and Red Knot recovery, requiring annual stopover population estimates. We estimated the 2025 passage population of Red Knots at Delaware Bay using a Bayesian analysis of a Jolly–Seber mark–resight model which accounts for population turnover and imperfect detection. We also evaluated change in migration timing between 2011 and 2025 with model-derived estimates of arrival at the Delaware Bay each year. The 2025 passage population was 54,043 individuals (95% credible interval: 47,926–61,928), an increase of approximately 17% over 2024 and only the second year since 2011 to exceed 50,000 individuals. Despite the increase, overlapping credible intervals across years indicate a stable stopover population. Migration timing has remained consistent, with 50% of the population typically arriving by 18 May and no evidence of advancement since 2011. These findings provide meaningful input for the ARM framework, supporting sustainable harvest of horseshoe crabs while maintaining adequate foraging opportunities for Red Knots and other shorebirds.

Prioritization is a central component of natural resource management because conservation needs routinely exceed available resources. Waterfowl and wetland conservation programs in North America are at the forefront of landscape-scale prioritization and transboundary management decisions due to the migratory nature of ducks, geese, and swans. The growing availability of geographic information systems (GIS) and geospatial technologies has accelerated the development of multi-objective landscape prioritization models, including applications of structured decision making and multi-criteria decision analysis to spatial planning for waterfowl and wetlands at the continental scale. However, regional managers and conservationists could benefit from flexibility in downscaling continental tools, selecting objectives, and assigning weights for rapid production of spatial prioritization models at smaller spatial scales without extensive computer coding or GIS analysis. We developed a spatial value model that prioritizes landscapes at sub-continental scales (e.g., states and provinces, bird conservation regions, etc.) and provides flexibility for users to select waterfowl conservation objectives of interest and weights. Our model can be used for direct downscaling of an existing continental geospatial model or further customized with region-specific geospatial data. We illustrate how regional prioritization can vary with the spatial scale selected by the user. The spatial value modeling framework and the downscaling tool presented here could increase the use of multi-criteria decision analysis and linear value modeling in spatial landscape prioritization, while also providing flexibility for selecting scales, objectives, and weights. Our spreadsheet tool was developed specifically for use by regional biologists, conservationists, and managers and does not require knowledge of GIS software (although results can be exported from the spreadsheet for spatial analysis using GIS). Together, the model outputs and the accompanying spreadsheet tool provide a bridge between continental waterfowl conservation and regional implementation, enabling rapid, stakeholder-driven, value-explicit prioritization.

Conservation of migratory birds throughout the full annual cycle requires a comprehensive understanding of abundance and distribution in interconnected breeding, migration, and wintering habitats. The Mountain Plover ( Anarhynchus montanus ) is a rare endemic breeder of the Rocky Mountain and Great Plains regions that migrates to wintering grounds in the southwestern USA and northern Mexico. Information regarding its wintering abundance and distribution, particularly in Texas, is limited. This study provides the first population estimate for Mountain Plovers wintering in Texas and examines factors influencing their land cover use. Through distance sampling surveys in six ecoregions of Texas, we estimated an annual wintering population of 3096 (95% CI 1464–6547) Mountain Plovers during 2019–2020, with the greatest abundances in the Southern Texas Plains and Western Gulf Coastal Plain ecoregions. The highest plover densities were in the Southern Texas Plains and Central Great Plains ecoregions. Most plovers were found in cultivated crops, particularly tilled fields and sod farms, and plovers preferentially selected crop fields without residual vegetation or stubble. Grass/hay fields were used less, perhaps because of tall vegetation. Our findings highlight the significance of Texas as a wintering area for Mountain Plovers and emphasize the importance of specific cropland habitats for this species. These results provide crucial insights for conservation and management efforts aimed at protecting Mountain Plovers throughout their annual cycle.

Baseline information about declining North American shorebird populations is essential to determine the effects of global warming at low-lying coastal areas of the Arctic and subarctic, where numerous taxa breed, and to assess population recovery throughout their range. We estimated population sizes on the Yukon-Kuskokwim Delta (YKD) in western Alaska on the eastern edge of the Bering Sea. We conducted ground-based surveys during 2015 and 2016 at 589 randomly selected plots from an area of 35,769 km(2). We used stratified random sampling in 8 physiographic strata and corrected population estimates using detection ratios derived from double sampling on a subset of plots. We detected 11,110 breeding individuals of 21 taxa. Western Sandpiper (Calidris mauri), Red-necked Phalarope (Phalaropus lobatus), Dunlin (subspecies C. alpina pacifica), and Wilson's Snipe (Gallinago delicata) were the most abundant taxa. We estimated that similar to 7 million individual shorebirds were breeding on the entire YKD in 2015 and 2016. Our surveys of this region provided robust population estimates (coefficient of variations <= 0.35) for 14 species. Our results indicate that the YKD supports a large proportion of North America's breeding populations of the Pacific Golden-Plover (Pluvialis fulva), the western population of a Whimbrel subspecies (Numenius phaeopus hudsonicus), a Bar-tailed Godwit subspecies (Limosa lapponica baueri), Black Turnstone (Arenaria melanocephala), a Dunlin subspecies (C. alpina pacifica), and Western Sandpiper. Our study highlights the importance of breeding shorebirds of this relatively pristine but climatically sensitive deltaic system. Estuaries and deltaic systems worldwide are rapidly being degraded by anthropogenic activities. Our population estimates can be used to refine prior North American population estimates, determine the effects of global warming, and evaluate conservation success by measuring population change over time.

Uncertainty, complexity, and dynamic changes present challenges for conservation and natural resource management. Evidence-based approaches grounded in reliable information and rigorous analysis can enhance the navigation of the uncertainties and trade-offs inherent in conservation problems. This study highlights the importance of collaborative efforts and evidence-based decision-making, specifically implementing the Resilience-Experimentalist school of adaptive management (RE-ARM), which emphasizes stakeholder involvement, shared understanding, and experimentation. Our goal was to develop an adaptive management framework to reduce the uncertainty around the use of prescribed fire to manage the habitat for eastern black rails (Laterallus jamaicensis jamaicensis) and mottled ducks (Anas fulvigula) in saltmarshes of the Gulf of Mexico. Supported by discussions at a series of workshops, we used a value of information analysis to select a fire management hypothesis to test, developed an influence diagram to represent the system under fire management, used the influence diagram to develop a Bayesian decision network (BDN), and conducted a power analysis to guide management experiments and monitoring. Value of information analysis identified fire return interval as the critical uncertainty. Our BDN provided valuable insight into how managers believe prescribed fire influences vegetation characteristics and how vegetation influences both eastern black rail occupancy and mottled duck abundance. The results of the power analysis indicated that a standard occupancy modeling framework was more useful to compare 2- and 5-year fire return intervals for black rails than two alternative designs (removal and conditional). Our BDN can be used to predict the probability of achieving the desirable vegetative response to increase the occupancy probability of black rails and abundance of mottled ducks, and monitoring data can be used to update the BDN (learn) and improve best management practices for prescribed burns (adapt). Linking the value of information, BDNs, and power analysis enhances our understanding of the system, improves management decision-making, and builds trust among scientists, interested parties, and decision-makers. This approach lays the groundwork for knowledge co-production and adaptive management.

Consideration of the full annual cycle population dynamics can provide useful insight for conservation efforts, but collecting data needed to estimate demographic parameters is often logistically difficult. For species that breed in remote areas, monitoring is often conducted during migratory stopover or at nonbreeding sites, and the recruitment rate of new breeding adults can be difficult to estimate directly. Here, we present an integrated population model that uses mark-resight and count data to estimate survival probability, population growth rate, and recruitment rate for an Arctic-breeding shorebird of conservation concern, the red knot (Calidris canutus rufa), from data collected during spring stopover in Delaware Bay, USA, from 2005 to 2018. At this site, red knots feed primarily on the eggs of spawning horseshoe crabs (Limulus polyphemus), a legally harvested species. We used this model to estimate the relationship between horseshoe crab abundance and red knot demographics, which informed a recent revision to the framework used to establish horseshoe crab harvest regulations. Our analysis indicates that the red knot population was most likely stable from 2005 to 2018 (average lambda = 1.03, 95% credible interval [CRI]: 0.961, 1.15) despite low recruitment rates (average rho = 0.088, 95% CRI: 0.012, 0.18). Adult survival probability was positively associated with horseshoe crab abundance in the same year (beta = 0.35, 95% CRI: 0.09, 0.63), but we found no effect of horseshoe crab abundance two years previously on recruitment of new adults (beta = -0.08, 95% CRI: -0.41, 0.38). Our approach demonstrates the utility of integrated population models for understanding population dynamics, even when data are only available from migratory stopover monitoring.

Summary Information about population sizes, trends, and habitat use is key for species conservation and management. The Buff-breasted Sandpiper Calidris subruficollis (BBSA) is a long-distance migratory shorebird that breeds in the Arctic and migrates to south-eastern South America, wintering in the grasslands of southern Brazil, Uruguay, and Argentina. Most studies of Nearctic migratory species occur in the Northern Hemisphere, but monitoring these species at non-breeding areas is crucial for conservation during this phase of the annual cycle. Our first objective was to estimate trends of BBSA at four key areas in southern Brazil during the non-breeding season. We surveyed for BBSA and measured vegetation height in most years from 2008/09 to 2019/20. We used hierarchical distance sampling models in which BBSA abundance and density were modelled as a function of vegetation height and corrected for detectability. Next, we used on-the-ground surveys combined with satellite imagery and habitat classification models to estimate BBSA population size in 2019/20 at two major non-breeding areas. We found that abundance and density were negatively affected by increasing vegetation height. Abundance fluctuated five- to eight-fold over the study period, with peaks in the middle of the study (2014/15). We estimated the BBSA wintering population size as 1,201 (95% credible interval [CI]: 637–1,946) birds in Torotama Island and 2,232 (95% CI: 1,199–3,584) in Lagoa do Peixe National Park during the 2019/20 austral summer. Although no pronounced trend was detected, BBSA abundance fluctuated greatly from year to year. Our results demonstrate that only two of the four key areas hold high densities of BBSA and highlight the positive effect of short grass on BBSA numbers. Short-grass coastal habitats used by BBSA are strongly influenced by livestock grazing and climate, and are expected to shrink in size with future development and climatic changes.

The value of information is a central concept in decision analysis, used to quantify how much the expected outcome of a decision would be improved if epistemic uncertainty could be resolved prior to committing to a course of action. One of the challenges, however, in quantitative analysis of the value of information is that the calculations are demanding, especially in requiring predictions of outcomes as a function of alternative actions and sources of uncertainty. However, the concept of value of information is important in early framing of some decisions, before such predictions are available. We propose a novel measure of the value of information based on constructed scales (CVOI), grounded in the algebra of the expected value of perfect information (EVPI), but requiring less of experts and analysts. The CVOI calculation decomposes EVPI into a contribution representing the relevance of the uncertainty to the decision and a contribution representing the magnitude of uncertainty; constructed ratio scales are then proposed for each contribution. We demonstrate the use of CVOI to identify research priorities related to migratory bird management in the face of climate change. Funding: This work was funded in part by the U.S. Geological Survey National Climate Adaptation Science Center.

Conservation planning for large ecosystems has multiple benefits but is often challenging to implement because of the multiple jurisdictions, species, and habitats involved. In addition, decision making at large spatial scales can be hampered because many approaches do not explicitly incorporate potentially competing values and concerns of stakeholders. After the Deepwater Horizon oil spill, establishing baselines was challenging because of (1) variation in study designs, (2) inconsistent use of explicit objectives and hypotheses, (3) inconsistent use of standardized monitoring protocols, and (4) variation in spatial and temporal scope associated with avian monitoring projects before the spill. Herein, we show how the Gulf of Mexico Avian Monitoring Network members used structured decision making to identify bird monitoring priorities. We used multiple tools and techniques to clearly define the problem and stakeholder objectives and to identify bird monitoring priorities at the scale of the entire northern Gulf of Mexico region. Although our example is specific to the northern Gulf of Mexico, this approach provides an example of how stakeholder values can be incorporated into the coordination process of broad-scale monitoring programs to address management, restoration, and scientific questions in other ecosystems and for other taxa. History: This paper was refereed. This paper was accepted for the Special Issue of INFORMS Journal on Applied Analytics—Decision Analysis. Funding: Thanks to the National Fish and Wildlife Foundation [Grant 324423], which supported A. Fournier as a postdoctoral research associate at Mississippi State University. M. Woodrey was supported by the U.S. Department of Agriculture, National Institute of Food and Agriculture, Hatch Project funds, the Mississippi Agricultural and Forestry Experiment Station, National Oceanographic and Atmospheric Administration [Grant NA16NOS4200088 to the Mississippi Department of Marine Resources’ Grand Bay National Estuarine Research Reserve], and the Mississippi Department of Marine Resources [Grant 8200025414]. This publication is a contribution of the Mississippi Agricultural and Forestry Experiment Station. T. Zenzal was supported by the National Oceanic and Atmospheric Administration RESTORE Act Science Program [Grant NA17NOS4510092].

Classifying species into risk categories is a ubiquitous process in conservation decision-making affecting regulatory procedures, conservation actions, and guiding resource allocation at global, national, and regional scales. However, monitoring programs often do not provide data required for accurate species classification decisions. Misclassification can lead to otherwise preventable species extinctions, undue regulatory burden, poor allocation of limited conservation resources, and can undermine species conservation legislation. We developed a framework that evaluates monitoring designs based on the ability to correctly inform a species classification decision, where minimizing the risk of misclassification is the central objective. We further evaluated monitoring designs by calculating the expected value of information and explored the relationship between statistical power to detect trends and misclassification. Our measure of misclassification risk, which can be tailored to the decision context, clarified the costs of over- and under-protection. High power to detect trends often corresponded to accurate species classification decisions. However, in several scenarios power to detect trends was low but the ability to correctly inform the classification decision was high. The value of information generally increased with monitoring intensity and quantified the tradeoffs between spatial and temporal replication. Our framework allows managers to assess monitoring program performance with direct implications for conservation decision-making. Our framework affords practitioners an opportunity to evaluate the effectiveness of monitoring programs a priori focusing on improving conservation decisions. We demonstrate that prioritizing monitoring to minimize misclassification errors can improve monitoring efficiency and conservation decision-making with considerable practical applications and benefits for species conservation.

Conservation decisions are often made in the face of uncertainty because the urgency to act can preclude delaying management while uncertainty is resolved. In this context, adaptive management is attractive, allowing simultaneous management and learning. An adaptive program design requires the identification of critical uncertainties that impede the choice of management action. Quantitative evaluation of critical uncertainty, using the expected value of information, may require more resources than are available in the early stages of conservation planning. Here, we demonstrate the use of a qualitative index to the value of information (QVoI) to prioritize which sources of uncertainty to reduce regarding the use of prescribed fire to benefit Eastern Black Rails (Laterallus jamaicensis jamaicensis), Yellow Rails (Coterminous noveboracensis), and Mottled Ducks (Anas fulvigula; hereafter, focal species) in high marshes of the U.S. Gulf of Mexico. Prescribed fire has been used as a management tool in Gulf of Mexico high marshes throughout the last 30+ years; however, effects of periodic burning on the focal species and the optimal conditions for burning marshes to improve habitat remain unknown. We followed a structured decision-making framework to develop conceptual models, which we then used to identify sources of uncertainty and articulate alternative hypotheses about prescribed fire in high marshes. We used QVoI to evaluate the sources of uncertainty based on their Magnitude, Relevance for decision-making, and Reducibility. We found that hypotheses related to the optimal fire return interval and season were the highest priorities for study, whereas hypotheses related to predation rates and interactions among management techniques were lowest. These results suggest that learning about the optimal fire frequency and season to benefit the focal species might produce the greatest management benefit. In this case study, we demonstrate that QVoI can help managers decide where to apply limited resources to learn which specific actions will result in a higher likelihood of achieving the desired management objectives. Further, we summarize the strengths and limitations of QVoI and outline recommendations for its future use for prioritizing research to reduce uncertainty about system dynamics and the effects of management actions.

Red Knots ( Calidris canutus rufa ) stop at Delaware Bay during northward migration to feed on eggs of horseshoe crabs ( Limulus polyphemus ). In the late 1990s and early 2000s, the number of Red Knots found at Delaware Bay dramatically declined from ~50,000 to ~13,000. Horseshoe crabs have been harvested for use as bait in eel and whelk fisheries since at least 1990, and some avian conservation biologists hypothesized that harvest levels in the 1990s prevented sufficient refueling for successful migration to the breeding grounds, nesting, and survival for the remainder of the annual cycle. Since 2013, the harvest of horseshoe crabs in the Delaware Bay region has been managed using an Adaptive Resource Management (ARM) framework. The objective of the ARM framework is to manage sustainable harvest of Delaware Bay horseshoe crabs while maintaining ecosystem integrity and supporting Red Knot recovery with adequate stopover habitat for Red Knots and other migrating shorebirds. For annual harvest recommendations, the ARM framework requires annual estimates of horseshoe crab population size and the Red Knot stopover population. We conducted a mark-recapture-resight investigation to estimate the passage population of Red Knots at Delaware Bay in 2021. We used a Bayesian analysis of a Jolly-Seber model, which accounts for turnover in the population and the probability of detection during surveys. The 2021 Red Knot mark-resight dataset included a total of 1,591 individual birds that were recorded at least one during mark-resight surveys at Delaware Bay in 2021. The passage population size in 2021 was estimated at 42,271 (95% credible interval: 35,948 – 55,210). Like 2020, the 2021 population estimate is slightly lower than the 2018 and 2019 estimates. The 2021 population size estimate will inform decision making for harvest recommendations in the next management cycle.

The North American Wetlands Conservation Act provides funding and administration for wetland management and conservation projects. The North American Wetland Conservation Fund, enabled in 1989 with the Act, provides financial resources. Resource allocation decisions are based, in part, on regional experts, particularly migratory bird Joint Ventures (JV; partnerships established under the North American Waterfowl Management Plan to help conserve the continent's waterfowl populations and habitats). The JVs evaluate funding proposals submitted within their respective regions each year and make funding recommendations to decision makers. Proposal evaluation procedures differ among JVs; however, it could be helpful to consider a transparent, repeatable, and data-driven framework for prioritization within regions. We used structured decision-making and linear additive value models for ranking proposals within JV regions. We used two JVs as case studies and constructed two different value models using JV-specific objectives and weights. The framework was developed through a collaborative process with JV staff and stakeholders. Models were written in Microsoft Excel. To test these models, we used six North American Wetlands Conservation Act proposals submitted to the Upper Mississippi/Great Lakes JV in 2016 and seven proposals submitted to the Gulf Coast JV in 2017. We compared proposal ranks assigned by the value model to ranks assigned by each JV's management board. Ranks assigned by the value model differed from ranks assigned by the board for the Upper Mississippi/Great Lakes JV, but not for the Gulf Coast JV. However, ranks from the value model could change markedly with different objective weights and value functions. The weighted linear value model was beneficial for ranking NAWCA proposals because it allows JVs to treat the ranking as a multiple objective problem and tailor the ranking to their specific regional concerns. We believe a structured decision-making approach could be adapted by JV staff to facilitate a systematic and transparent process for proposal ranking by their management boards.

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex in Maine. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of two marsh management units within the refuge complex, totaling about 47 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to $9,545, and may continue to increase at a lower rate with further expenditures. Potential management actions in optimal 1U.S. Geological Survey. 2U.S. Fish and Wildlife Service. 3U.S. Fish and Wildlife Service, retired. portfolios at total costs less than or equal to $9,545 included removing dikes to restore tidal flow in the Gouldsboro Bay management unit and installing runnels to improve surfacewater drainage in the Sawyers Marsh management unit. The potential management benefits were derived from expected increases in the numbers of tidal marsh obligate breeding birds and density of spiders (as an indicator of trophic health), reduced duration of flooding, and increased capacity of marsh elevation to keep pace with sea-level rise. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Maine Coastal Islands National Wildlife Refuge Complex that can be updated for implementation as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge complex.

Natural resource management decisions are often made in the face of uncertainty. The question for the decision maker is whether the uncertainty is an impediment to the decision and, if so, whether it is worth reducing uncertainty before or while implementing actions. Value of information (VoI) methods are decision analytical tools to evaluate the benefit to the decision maker of resolving uncertainty. These methods, however, require quantitative predictions of the outcomes as a function of management alternatives and uncertainty, in which predictions which may not be available at early stages of decision prototyping. Here we describe the first participatory application of a new qualitative approach to VoI in an adaptive management workshop for Atlantic Coast eastern black rail populations. The eastern black rail is a small, cryptic marsh bird that was recently listed as federally threatened, with extremely little demographic data available. Workshop participants developed conceptual models and nine hypotheses related to the effects of habitat management alternatives on black rail demography. Here, we describe the qualitative VoI framework, how it was implemented in the workshop, and the analysis outcomes, and describe the benefits of qualitative VoI in the context of adaptive management and co-production of conservation science.

Understanding the effects of migratory stopover site conditions on both demographic rates and migratory behaviors is critical for interpreting changes in passage population sizes at stopover sites and predicting responses to future changes and conservation actions. We used a Bayesian formulation of the open robust design model to analyze mark-resight observations of three migratory shorebird species using Delaware Bay, USA during spring stopover from 2005 to 2018. We tested for an effect of stopover food availability and weather conditions on survival probability and the probability of returning to this site in the next year and found species differences in these relationships. After years with greater food availability, red knot Calidris canutus rufa had higher survival probability but ruddy turnstone Arenaria interpres were more likely to return to the site. Estimates of within-year probabilities of arrival and persistence at the stopover site showed relatively consistent migration schedules for ruddy turnstone, but more interannual variation for red knot and sanderling Calidris alba. Shorebird use of this site typically peaked during May 26-28, but the estimated proportion of the population present during this period varied dramatically among years for red knot (range: 0.07-0.59) but less so for ruddy turnstone and sanderling. This demonstrates that both the proportion of the flyway population using this stopover site and the proportion present during a given sampling period vary among years, and both should be considered in analyzing and interpreting monitoring data. Stopover conditions can influence both migratory behavior and demographics, underscoring the importance of flyway-wide monitoring.

First posted May 28, 2021 For additional information, contact: Director, Eastern Ecological Science Center U.S. Geological Survey 11649 Leetown Road Kearneysville, WV 25430Contact Pubs Warehouse Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Edwin B. Forsythe National Wildlife Refuge in New Jersey. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of 23 marsh management units within the refuge and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to about \$980,000, but that further expenditures may yield diminishing return on investment. Potential management actions in optimal portfolios at total costs less than \$980,000 included applying sediment to the marsh surface to increase elevation in five marsh management units, digging runnels on the marsh surface to improve drainage in five marsh management units, and breaching roads and berms to improve tidal flow in five marsh management units. The potential management benefits were derived from expected reduction in the duration of surface flooding, improved capacity for marsh elevation to keep pace with sea-level rise and increases in numbers of spiders (as an indicator of trophic health), tidal marsh obligate birds, and wintering American black ducks. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Edwin B. Forsythe National Wildlife Refuge that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.

ABSTRACT Many shorebirds rely on small numbers of staging sites during long annual migrations. Numerous shorebird species are declining and understanding the importance of these staging sites is important for successful conservation. We surveyed endangered rufa red knots ( Calidris canutus rufa ) staging in James Bay, Ontario, Canada, during southbound migration in 2017 and 2018. We used mark‐resight data and count data in an integrated Bayesian analysis to quantify migration phenology, estimate passage population size, and model the age structure of the stopover population. Many adult red knots arrived in James Bay in a single wave in early August in 2017, whereas adult red knots arrived in multiple smaller waves in July and mid‐August in 2018. These waves may correspond with breeding phenology where more red knots bred successfully and arrived in one large event in 2017 and the higher number of earlier arrivals in July 2018 may have been failed breeders. We included a binomial generalized linear model in the integrated analysis to estimate that 20% and 10% of staging red knots were juveniles in 2017 and 2018, respectively. In future applications, this method could provide a metric to assess breeding performance and develop our understanding of its role in population declines. Overall, we estimated that up to 23% of the estimated rufa red knot population staged in southwestern James Bay for an average of 10–12 days. The region is a key staging site for endangered red knots and could be included in conservation planning. © 2021 The Wildlife Society.

The avian conservation community struggles to design and implement large scale, long-term coordinated bird monitoring programs within the northern Gulf of Mexico due to the complexity of the conservation enterprise in the region; this complexity arises from the diverse stakeholders, multiple jurisdictions, complex ecological processes, myriad habitats, and over 500 species of birds using the region for at least some part of their annual cycle. In addition, long-term monitoring over large spatial scales is difficult because of the need for monitoring data to both (1) evaluate management and restoration outcomes, and (2) provide reliable information about the status and trends of bird populations over time. To address these challenges, the Gulf of Mexico Avian Monitoring Network developed a problem statement: “How can a cost-effective monitoring strategy for the Gulf Coast bird community and ecosystem be developed that evaluates ongoing conservation activities and chronic and acute threats; maximizes learning; and is flexible and holistic enough to detect novel ecological threats and evaluate new and emerging conservation activities?” A structured decision-making framework was then used to articulate and quantify stakeholder values related to the problem statement. One use of the stakeholder values was to develop a regional, strategic plan for bird monitoring, which is presented elsewhere. A formal and complete decision support tool for conservation investments in monitoring and research guided by the stakeholder values is presented in this report. The technical aspects of the stakeholder value model and a portfolio analysis that could be used to guide decision making when allocating resources for monitoring activities is described. Whereas the decision analysis presented here could be useful to any decision maker faced with difficult choices about resource allocation, it is designed for decision makers who request monitoring study proposals and then determine which combination of proposals to fund. The portfolio decision support tool is designed to help funding agencies and organizations identify resource allocation strategies to maximize stated objectives. To begin the decision analysis, an objectives hierarchy and quantitative performance metrics from the values of the Gulf of Mexico bird conservation community were created by a panel of regional stakeholders. Each fundamental objective and sub-objective in the hierarchy is composed of several performance metrics. To test the decision support tool, the authors evaluated a combination of monitoring study proposals written for the region and simulated proposals. Each proposal was scored against the performance metrics and used multi-attribute utility theory to combine the multiple objectives into a measure of total monitoring benefit. The total monitoring benefit and costs of each proposal were then used in a constrained optimization routine to identify optimal monitoring portfolios, Structured Decision Making and Optimal Bird Monitoring in the Northern Gulf of Mexico By Auriel M.V. Fournier1+, R. Randy Wilson2, James E. Lyons3, Jeffrey S. Gleason4, Evan M. Adams5, Laurel M. Barnhill6, Janell M. Brush7, Robert J. Cooper8, Stephen J. DeMaso9, Melanie J.L. Driscoll10, Mitchell J. Eaton3, Peter C. Frederick11, Michael G. Just12, Michael A. Seymour13, John M. Tirpak14, and Mark S. Woodrey1,15 1 Mississippi State University, Biloxi, Mississippi 2 U.S. Fish and Wildlife Service, Jackson, Mississippi 3 U.S. Geological Survey 4 U.S. Fish and Wildlife Service, Chiefland, Florida 5 Biodiversity Research Institute, Portland, Maine 6 U.S. Fish and Wildlife Service, Atlanta, Georgia 7 Florida Fish and Wildlife Conservation Commission, Gainesville, Florida 8 University of Georgia, Athens, Georgia 9 U.S. Fish and Wildlife Service, Lafayette, Louisiana 10 Baton Rouge, Louisiana 11 University of Florida, Gainesville, Florida 12 North Carolina State University, Raleigh, North Carolina 13 Louisiana Department of Wildlife and Fisheries, Baton Rouge, Louisiana 14 U.S. Fish and Wildlife Service, Lafayette, Louisiana 15 Grand Bay National Estuarine Research Reserve, Moss Point, Mississippi + Current address: Forbes Biological Station–Bellrose Waterfowl Research Center, Illinois Natural History Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Havana, Illinois 2 Structured Decision Making and Optimal Bird Monitoring in the Northern Gulf of Mexico that is, a combination of activities that maximizes monitoring benefits while meeting cost and other constraints of interest to stakeholders. A graphical solution based on the concept of Pareto efficiency, which is useful in situations when cost constraints and exact budgets are not known, is also provided. Finally, an evaluation of the sensitivity of the decision-making framework to the weights assigned to objectives by stakeholders is included. This decision support tool allows decision makers to identify an optimal suite of monitoring proposals with a transparent portfolio analysis that includes user-defined constraints (such as costs).