Values for area of sustainable forest habitat for each species were obtained as the predicted occupied proportion of each 900 square meter pixel (i.e., occupancy probability x 900) within all forest patches deemed large enough to harbor a sustainable population of the species. The area required for a sustainable population of each species was derived from credible intervals associated with population trends from historical (1966-2015) BBS data (Sauer and others, 2017). For each silvicolous bird species in the Mississippi Alluvial Valley, we assumed the minimum sustainable population was the number of birds needed to ensure ≤1% probability that the population would be extirpated (i.e., drop below a quasi-extinction threshold) during a 100-year period wherein annual population change was randomly selected from the credible interval associated with each species’ population trend. We used the mean of 500 simulation replicates conducted in R (Version 3.4.4; https://www.r-project.org/) as the presumed minimum sustainable population for each species. We arbitrarily set the quasi-extinction threshold at 25 breeding pairs. Because species with credible intervals associated with their trend estimates that were inclusively positive never declined in population, by default these species had a minimum sustainable population of 25 pairs.

Values for area of sustainable forest habitat for each species were obtained as the predicted occupied proportion of each 900 square meter pixel (i.e., occupancy probability x 900) within all forest patches deemed large enough to harbor a sustainable population of the species. The area required for a sustainable population of each species was derived from credible intervals associated with population trends from historical (1966-2015) BBS data (Sauer and others, 2017). For each silvicolous bird species in the Mississippi Alluvial Valley, we assumed the minimum sustainable population was the number of birds needed to ensure ≤1% probability that the population would be extirpated (i.e., drop below a quasi-extinction threshold) during a 100-year period wherein annual population change was randomly selected from the credible interval associated with each species’ population trend. We used the mean of 500 simulation replicates conducted in R (Version 3.4.4; https://www.r-project.org/) as the presumed minimum sustainable population for each species. We arbitrarily set the quasi-extinction threshold at 25 breeding pairs. Because species with credible intervals associated with their trend estimates that were inclusively positive never declined in population, by default these species had a minimum sustainable population of 25 pairs.

Values for area of occupied habitat by each species were obtained as the predicted occupied proportion of each 900 square meter pixel (i.e., occupancy probability x 900) for all habitats, except permanent water, within the Mississippi Alluvial Valley Bird Conservation Region.

Values for area of occupied habitat by each species were obtained as the predicted occupied proportion of each 900 square meter pixel (i.e., occupancy probability x 900) for all habitats, except permanent water, within the Mississippi Alluvial Valley Bird Conservation Region.

Values for predicted probabilities of avian species occupancy were determined using colonization-extinction models (MacKenzie and others, 2003) as implemented in R (Version 3.4.4; https://www.r-project.org/) via the ‘colext’ function of the Unmarked package (Version 0.12-0; Fiske and Chandler 2011). Performance of a null model (without covariates) and 153 additional models that assessed the effects of geographic coordinates and habitat context covariates were evaluated using Akaike information criteria (AIC; Burnham and Anderson, 2002). When more than one model had substantial support, their respective model weights were used to spatially predict occupancy relative to covariate influence. Predictive model covariates and weights are provided in Appendix 4 (Twedt and Mini, 2020).

Values for predicted probabilities of avian species occupancy were determined using colonization-extinction models (MacKenzie and others, 2003) as implemented in R (Version 3.4.4; https://www.r-project.org/) via the ‘colext’ function of the Unmarked package (Version 0.12-0; Fiske and Chandler 2011). Performance of a null model (without covariates) and 153 additional models that assessed the effects of geographic coordinates and habitat context covariates were evaluated using Akaike information criteria (AIC; Burnham and Anderson, 2002). When more than one model had substantial support, their respective model weights were used to spatially predict occupancy relative to covariate influence. Predictive model covariates and weights are provided in Appendix 4 (Twedt and Mini, 2020).

Based on forest patch area, location, and hydrologic influence, we ranked the purported need of forest patches for additional conservation-protection. Qualities for higher ranking included forest patches with & greater than 2000 ha of core-forest that was more than 250 m from an edge, forest patches within high priority areas for reforestation, and forest patches with less propensity for flooding. Digital data are provided for: 1. Boundary of the Mississippi Alluvial Valley study area. 2. Forest cover (circa 2015) used to for determination of forest area in need of conservation protection. 3. The conservation estate (circa 2019) that had conservation protection by virtue of ownership, easement, or servitude. 4. Reforestation priority areas used to identify location of forests with increased need for forest protection. 5. Priority of forest areas for increased conservation protection.

Based on forest patch area, location, and hydrologic influence, we ranked the purported need of forest patches for additional conservation-protection. Qualities for higher ranking included forest patches with & greater than 2000 ha of core-forest that was more than 250 m from an edge, forest patches within high priority areas for reforestation, and forest patches with less propensity for flooding. Digital data are provided for: 1. Boundary of the Mississippi Alluvial Valley study area. 2. Forest cover (circa 2015) used to for determination of forest area in need of conservation protection. 3. The conservation estate (circa 2019) that had conservation protection by virtue of ownership, easement, or servitude. 4. Reforestation priority areas used to identify location of forests with increased need for forest protection. 5. Priority of forest areas for increased conservation protection.

These data pertain to bird point surveys collected from 30 April 2016 to 12 May 2016 and 23 May 2016 to 25 June 2016 at four bottomland hardwood restoration sites in northeastern Indiana. The data are a single monitoring occasion with the purpose of documenting bird communities across these sites. During the time of collection, sites contained areas of hardwood planting ranging in age from 2 to 22 years, mature forest, old fields, and cropland. Each site was surveyed at multiple, fixed bird survey points; each point was visited at least 7 times. Bird point surveys were conducted between sunrise and 11:00 Central Daylight Time, lasted 5 minutes, and aimed to record all bird species seen and heard within 100 meters of the survey point center. Taxonomic and other classification information is provided for each bird taxon. Other classifications include designation of species as Partners in Flight regional conservation concern species and/or interior forest specialists. Also given are the spatial coordinates of each survey point with a rough habitat classification of each point, either woody plant-dominated or grassland-like. Bird survey data contain detection and non-detection data for 106 bird taxa within 100 meters during each survey, as well as observations of flyover species. Also included is R code to resample the data to create resampled datasets for use in rarefaction-based analyses. Values within the resampled dataset include site, number of points surveyed (samples), number of survey visits per point (subsamples), cumulative number of resampling occasions, presence of grassland-like habitat points among the samples within a resampling occasion., presence of woody plant-dominated habitat points among the samples, and detection/non-detection of different landbird species.