The eastern black rail (Laterallus jamaicensis jamaicensis; hereafter rail) is a small, cryptic marshbird that was recently listed as threatened under the U.S. Endangered Species Act. We organized a rapid prototyping workshop to initiate development of an adaptive management for rails on the Atlantic Coast. The in-person workshop spanned 2.5 days and was held in Titusville, Florida in January 2020. Workshop participants, comprised of species experts and land managers of rail habitats, chose to focus the framework on testing habitat management techniques to maximize rail occupancy, in which uncertainties could be reduced through a combination of field management experiments and coordinated monitoring. We used the qualitative value of information to prioritize uncertainties (stated as alternative hypotheses developed by participants in habitat-based breakout groups) that could serve as the basis for experiments within the adaptive management framework. Qualitative value of information (QVoI) is a newly-developed decision analysis tool that scores uncertainties in three areas: (1) Magnitude of uncertainty which reflects the strength of theoretical foundation and empirical support of the hypothesized relationship; (2) Relevance to management decisions which indicates how likely the preferred management alternative is to change if the uncertainty were resolved; and (3) Reducibility which is the degree to which the uncertainty could be resolved through research and monitoring. Magnitude is scored on a scale of 0-4, whereas Relevance and Reducibility can vary from 0-3. These data are the anonymized workshop participant (n=26) scores for nine hypotheses focused on testing habitat management techniques, to determine which hypotheses should serve as the basis for management experiments in an adaptive management framework. The data are contained in a .csv file that can be opened using a spreadsheet program such as Microsoft Excel, or read into a statistical analysis program such as Program R.

The American alligator (Alligator mississippiensis) is a species of ecological and economic importance in the southeastern United States. Within South Carolina, alligators are subject to private and public harvest programs, as well as nuisance removal. These management activities can have different impacts across alligator size classes that may not be apparent through widely-used monitoring techniques such as nightlight surveys. We synthesized multiple datasets within an integrated population model (IPM) to estimate size class-specific survival and abundance estimates, that would not be estimable through separate, non-integrated modeling frameworks. The IPM framework included a multistate mark-recapture-recovery model that used mark-recapture-recovery data from the Tom Yawkey Wildlife Center and growth transition probabilities that were estimated outside of the IPM framework. The IPM also included a state-space count model, which used nightlight survey counts of alligtaors from two survey routes: 1) Great Pee Dee and Waccamaw Rivers; and 2) South Santee Rivers. The IPM modeling framework also used mean clutch size data from the Tom Yawkey Wildlife Center and public and private harvest data within the state model. Lastly, we evaluated the effects of capture effort on capture probability, as well as the effects of water temperature and relative water level on count detection probability, and provide all covariate datasets. Our IPM framework determined that size class-specific survival rates were relatively high for all non-hatchling size classes, and abundance trends differed between the two nightlight survey sites.

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