Sustaining healthy populations of waterbirds that migrate long distances is a major challenge for land managers. Integrated Waterbird Management and Monitoring (IWMM) is helping managers meet that challenge through a multi-scaled conservation approach that integrates monitoring, modeling, and decision support to optimize wetland management in ways that support continental populations of waterbirds. The program focuses on waterfowl, shorebirds and wading birds during migration and winter, and brings together managers, scientists and conservation partners from multiple regions. Essential elements of the program include goals in 3 focal areas: 1) Modeling and Decision Support, 2) Monitoring and 3) Data Management.
Modeling and Decision Support
To develop scientifically rigorous, quantitative models linking alternative habitat management decisions to anticipated outcomes for waterbirds. Key components are:
- An integrated model that links and optimizes management decisions at three spatial scales: local, regional and flyway
- A local decision support model that guides and informs the coordinated management of habitat at multiple units across a landscape to maximize benefits for waterbirds.
To provide protocols for data collection that will inform decision support models for waterbird management, and that facilitate an adaptive management approach. These protocols:
- Track waterbird use, habitat conditions and management actions simultaneously
- Standardize and coordinate waterbird and habitat monitoring for potential aggregation at larger scales
- Provide data for testing alternative models, updating parameter estimates and evaluating habitat management effectiveness relative to waterbird management objectives
To provide a centralized online database that stores, manages, and reports waterbird, habitat, and management action data for management units located across multiple flyways.
- The database is a thematic node of the Avian Knowledge Network that supports station-level monitoring, simplifies data entry, and enhances decision making, data sharing and reporting capabilities.
The Science Behind IWMM
The Migration Model
IWMM has developed an ecological process model that simulates waterbird migration and links survival during this period to distribution of kilocalories available across the landscape. To “migrate” birds across the continent, the model incorporates GIS inputs (e.g., landcover, breeding and wintering range maps, population estimates, roosting quality, forage availability), and information from published studies of waterfowl behavior and natural history (e.g., food habits, flight speeds, travel distances).
The GIS layers are integrated to summarize quality of area at a node scale (nodes are 20×20 miles in size). The model produces a map of kcals available for each species for which it is run, then simulates bird movement through the flyway based on parameters from the literature. The model is currently parameterized for mallards but could be adapted to model migration in other waterfowl, shorebirds and waders. Model output can inform flyway scale management decisions by identifying areas on the landscape that should be prioritized for conservation because of their influence on migratory success. For example, removing energy one “node” at a time from the Atlantic Flyway suggested coastal areas between New Jersey and North Carolina, including Chesapeake Bay and the North Carolina piedmont, are essential locations for efficient migration and increasing survivorship during spring migration (Figure 1).
For the regional scale, the migration model can be used to identify which set of sites is most important for each waterbird guild. For the local scale, it identifies which guild a site should focus management on, given the site’s placement within the flyway.
To evaluate how well the model replicates empirical distribution patterns of waterbirds and the frequency and distance of typical migration movements, the IWMM Technical Team conducted model validation tests. The validation exercise indicated good agreement between bird-use days as estimated by the migration model and those calculated from eBird data for Mallards, based on more than 1,000 areas where this comparison could be made. The model has been peer-reviewed and a paper describing the modeling process and validation was published in 2016. A summary of that paper can be viewed here. Plans are now underway to apply the model to evaluate the importance of National Wildlife Refuge lands to migrating waterfowl.
Wetland Management Planning and Decision Support
To assist managers at the local scale, IWMM has developed a model that helps managers coordinate habitat management actions across multiple managed units to benefit waterbirds while also considering costs and other constraints. The model uses a Structured Decision Making (SDM) framework to identify management alternatives, or “portfolios”, different collections of management actions that could be employed across impoundments (Figure 2). The benefits of individual portfolios are evaluated, and the collection of management actions that maximizes benefits to waterbirds with respect to constraints is identified.The wetland manager can then use this portfolio to guide and coordinate management actions, and use IWMM monitoring to evaluate response to management, update model parameter estimates and test alternative models.
This decision support for wetland management has been developed through pilot projects at two national wildlife refuges, Mattamuskeet NWR in NC and Clarence Cannon in MO. For both projects, final case study reports have been prepared. IWMM is currently exploring strategies for making this modeling approach more widely available.
IWMM undertook an extensive pilot phase that began in 2010 for testing, revising and improving waterbird and habitat monitoring protocols. During this time, IWMM received feedback from monitoring participants and conducted field studies to validate and improve protocol (s). IWMM also created a National Protocol framework to guide use of the monitoring component by cooperators within the National Wildlife Refuge System (NWR). This framework enables refuges to develop site-specific protocols that are compliant with the NWR System’s recently updated inventory and monitoring policy. The IWMM monitoring protocol underwent an intense peer-review process which led to further refinements of the protocol, and was approved as a National Protocol Framework by the USFWS’s Inventory and Monitoring Program in January 2015.
Habitat Protocol Validation
In 2012, IWMM conducted a habitat protocol validation study focused on the performance of IWMM’s pilot approach to rapid visual estimates of habitat features. Visual estimates were compared to assessments made via traditional vegetation quadrats and the classification of high resolution color-Infrared aerial images. Along with participant feedback, the 2012 study led to major changes in IWMM’s habitat sampling approach. Results of this study were published in 2016 and the study is available here. A summary of the publication with highlights of the study is available here.
A second validation study targeting the newly revised protocol was initiated in the summer of 2014. This assessment will compare the performance of the revised protocol’s seed production index against quantitative assessments for moist-soil plants. The study will also evaluate the performance of unit-scale habitat type cover and vegetation to water interspersion estimates against products derived from high resolution color-Infrared aerial images. The field data collection, quantitative seed estimates, and remote sensing captures are complete. Current analyses are expected to produce two manuscripts that will be submitted to peer-reviewed journals.
Using Monitoring Data to Improve Inferences About Migration
IWMM is one of the few monitoring programs to collect the kind of large-scale, local level data necessary for drawing inferences about migratory patterns and processes (Figure 3). IWMM has quantitative scientists analyzing these data to elucidate the connection between habitat conditions and waterfowl abundance. These data identify landscape features to which migrating dabbling ducks respond, and can inform management decisions both locally and regionally (Publication Summary or full publication).