Geology topics

Mark E Seamans

Publications and source records attributed to Mark E Seamans.

3 recordsLinked to original sources

USGS2025

Developing research tools for demographic study of Rhynchophanes mccownii (thick-billed longspurs)

Like numerous other North American grassland bird species, Rhynchophanes mccownii (thick-billed longspur) has experienced severe population declines in the last 50 years. Little is known about population-limiting factors, and knowledge gaps limit conservation efforts on the species; however, before research studies aimed at improving conservation and management actions can be developed, other research must resolve notable knowledge gaps that exist in field techniques for efficient and effective large-scale demographic studies. We examined several techniques for the capture, marking (metal, color bands, and transmitters), and reencountering (resights and telemetry) of thick-billed longspurs in croplands and prairies in Valley County, Montana, during the 2022 and 2023 breeding seasons. Our goal was to evaluate the feasibility of obtaining within- and between-season resights of individual thick-billed longspurs using optical equipment and cameras, transmitter receivers, and the Motus automatic receiving station network. This report includes observations and insights that may aid researchers embarking on future demographic studies of thick-billed longspurs, as well as other grassland birds that provide similar research challenges.

Open-File Report↗

USGS2021

American Woodcock singing-ground survey: Comparison of four models for trend in population size

Wildlife biologists monitor the status and trends of American woodcock Scolopax minor populations in the eastern and central United States and Canada via a singing-ground survey, conducted just after sunset along roadsides in spring. Annual analyses of the survey produce estimates of trend and annual indexes of abundance for 25 states and provinces, management regions, and survey-wide. In recent years, researchers have used a log-linear hierarchical model that defines year effects as random effects in the context of a slope parameter (the S model) to model population change. Recently, researchers have proposed alternative models suitable for analysis of singing-ground survey data. Analysis of a similar roadside survey, the North American Breeding Bird Survey, has indicated that alternative models are preferable for almost all species analyzed in the Breeding Bird Survey. Here, we use leave-one-out cross-validation to compare model fit for the present singing-ground survey model to fits of three alternative models, including a model that describes population change as the difference in expected counts between successive years (the D model) and two models that include t -distributed extra-Poisson overdispersion effects (H models) as opposed to normally distributed extra-Poisson overdispersion. Leave-one-out cross-validation results indicate that the Bayesian predictive information criterion favored the D model, but a pairwise t -test indicated that the D model was not significantly better-fitting to singing-ground survey data than the S model. The H models are not preferable to the alternatives with normally distributed overdispersion. All models provided generally similar estimates of trend and annual indexes suggesting that, within this model set, choice of model will not lead to alternative conclusions regarding population change. However, as in Breeding Bird Survey analyses, we note a tendency for S model results to provide slightly more extreme estimates of trend relative to D models. We recommend use of the D model for future singing-ground survey analyses.

Eastern and Central United States and Canada↗

USGS2009

Dynamic models for problems of species occurrence with multiple states

Recent extensions of occupancy modeling have focused not only on the distribution of species over space, but also on additional state variables (e.g., reproducing or not, with or without disease organisms, relative abundance categories) that provide extra information about occupied sites. These biologist-driven extensions are characterized by ambiguity in both species presence and correct state classification, caused by imperfect detection. We first show the relationships between independently published approaches to the modeling of multistate occupancy. We then extend the pattern-based modeling to the case of sampling over multiple seasons or years in order to estimate state transition probabilities associated with system dynamics. The methodology and its potential for addressing relevant ecological questions are demonstrated using both maximum likelihood (occupancy and successful reproduction dynamics of California Spotted Owl) and Markov chain Monte Carlo estimation approaches (changes in relative abundance of green frogs in Maryland). Just as multistate capture–recapture modeling has revolutionized the study of individual marked animals, we believe that multistate occupancy modeling will dramatically increase our ability to address interesting questions about ecological processes underlying population-level dynamics.

Ecology↗