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Rebecca Kolstrom

Publications and source records attributed to Rebecca Kolstrom.

3 recordsLinked to original sources

Developing a range-wide sampling framework for endangered species: A case study with light-footed Ridgway’s rail

Monitoring provides the foundation for evaluating recovery of endangered species, yet many species lack monitoring programs designed to integrate a species’ unique attributes, specific monitoring objectives, and principles of statistical sampling theory. We developed a framework for monitoring and assessment of endangered light-footed Ridgway’s rails ( Rallus obsoletus levipes ) across their U.S. range, relative to multi-scale recovery goals. We created spatially explicit sample units and a sampling frame covering all potential habitat to facilitate range-wide probability sampling, and also built a model of the call-broadcast process commonly used to survey marsh birds that included heterogeneity in availability for detection and conditional detectability for each bird during each survey. We used the model to simulate 96 sampling strategies that included different levels of replication, multiple approaches for sample allocation amongst strata, and both simple random and weighted probability sampling (i.e., weights proportional to local rail abundance) of sample units within strata. Effective monitoring surveyed ≥20–30% of the sampling frame on ≥3 occasions, with weighted sample selection and more targeted sampling (50% of units) for strata that are key to species recovery. We also tested Bayesian N-mixture models for estimating abundance and show that multiple models provide reasonable estimates. This work lays the foundation for statistical sampling and multi-scale population estimation for an endangered bird, and for refinement of abundance estimation models. Moreover, this work provides a replicable process for building customized and statistically defensible sampling frameworks to assess recovery of endangered species that can used for other sensitive species.

California

Using a structured decision analysis to evaluate bald eagle vital signs monitoring in Southwest Alaska National Parks

1. Monitoring programs can benefit from an adaptive monitoring approach, where key decisions about why, where, what, and how to monitor are revisited periodically in order to ensure programmatic relevancy. 2. The National Park Service (NPS) monitors status and trends of Vital Signs to evaluate compliance with the NPS mission. Although abundant, The Southwest Alaska Network (SWAN) monitors bald eagles because of their inherent importance to park visitors and role as an important ecological indicator. Our goal is to identify an optimal monitoring program that may be standardized among participating parks. 3. We gathered an expert panel of scientists and managers, and implemented a Delphi Process to gather information about the bald eagle monitoring program. Panelists generated a list of means objectives for the monitoring program: minimizing cost, minimizing effort, maximizing the ability to detect change in bald eagle populations, and maximizing the amount of accurate information collected about bald eagles. 4. We used a swing-weighting technique to assign importance to each objective. Collecting accurate information about bald eagles was considered the most important means objective. 5. Combining panelist-generated information with objective importance, we analyzed the scenarios and defined the optimal decision using linear value modeling. Through our analysis, we found that a “Comprehensive” monitoring scenario, comprised of all feasible monitoring metrics is the optimal monitoring scenario. Even with greatly increased cost, the Comprehensive monitoring scenario remains the best solution. 6. We suggest further exploration of the cost and effort required for the Comprehensive scenario, to determine if it is in the parks’ best interest to begin monitoring additional metrics.

Alaska

Using the Delphi process to gather information from a Bald Eagle expert panel

Bald eagle ( Haliaeetus leucocephalus ) populations are classified by the Southwest Alaska Network (SWAN) of the National Park Service as a vital sign of biological integrity, largely because of their importance as an indicator species for environmental contaminants and human disturbance. Though Bald Eagles are plentiful in Alaska, it is still imperative to have a monitoring plan that allows for the estimation of population sizes and detection of significant changes in populations. Currently, Bald Eagles are monitored in Kenai Fjords National Park, Katmai National Park and Preserve, Lake Clark National Park and Preserve, and Wrangell – St. Elias National Park, but each park uses different monitoring procedures and evaluation criteria. This makes it difficult for scientists and managers to compare data, detect changes in overall populations, and make effective management decisions. Our research is using a formal structured decision-making process to ensure that the Bald Eagle monitoring conducted by the parks is standardized and meets programmatic goals and objectives. We implemented a Delphi process, which is an iterative survey technique that is used to gather expert opinion. We used online questionnaires to gather information and opinions from National Park Service scientists and managers, eagle experts, and other interested parties. We identified important stressors and feasible monitoring metrics, which were tied to the means objectives for the Bald Eagle monitoring program: minimize cost, minimize effort, maximize ability to detect change in populations, and maximize accurate information about Bald Eagles. We will also analyze monitoring metrics using a consequence table, which determines the performance of each objective in terms of the means objectives chosen by expert panelists. This information will help to create a more accurate conceptual model of the system to guide development of a Bald Eagle monitoring program that can be standardized among Southwest Alaska National Parks.

Alaska