This data set contains sensitive biological resource data for wading birds, shorebirds, waterfowl, raptors, diving birds, seabirds, passerine birds, and gulls and terns in Maryland. Vector polygons in this data set represent bird nesting, feeding, migratory staging, and wintering sites. Species-specific abundance, seasonality, status, life history, and source information are stored in relational data tables (described below) designed to be used in conjunction with this spatial data layer.This data set comprises a portion of the Environmental Sensitivity Index (ESI) data for Maryland. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. See also the NESTS (Nest Points) data layer, part of the larger Maryland ESI database, for additional bird information.

Seabird species worldwide are integral to both marine and terrestrial environments, connecting the two systems by transporting vast quantities of marine-derived nutrients and pollutants to terrestrial breeding, roosting, and nesting grounds via the deposition of guano and other allochthonous inputs (e.g., eggs, feathers). We conducted a systematic review and meta-analysis and provide insight into what types of nutrients and pollutants seabirds are transporting, the influence these subsidies are having on recipient environments, with a particular focus on soil, and what may happen if seabird populations decline. The addition of guano to colony soils substantially increased nutrient levels compared to control soils for all seabirds studied, with cascading positive effects observed across a range of habitats. Deposited guano sometimes led to negative impacts, such a guanotrophication, or guano-induced eutrophication, which was often observed where there was an excess of guano or in areas with high seabird densities. While the literature describing nutrients transported by seabirds is extensive, literature regarding pollutant transfer is comparatively limited, with a focus on toxic and bioaccumulative metals. Research on persistent organic pollutants and plastics transported by seabirds is likely to increase in coming years. Studies were limited geographically, with hotspots of research activity in a few locations, but data were lacking from large regions around the world. Studies were also limited to seabird species generally listed as Least Concern on the IUCN Red List. As seabird populations are impacted by multiple threats and steep declines have been observed for many species worldwide, gaps in the literature are particularly concerning. The loss of seabirds will impact nutrient cycling at localised levels and potentially on a global scale as well, yet it is unknown what may truly happen to areas that rely on seabirds if these populations disappear. The information in this record includes three spreadsheets and R code. Descriptions are included below: - The spreadsheets contain all information extracted from the publications that were critically reviewed (n = 181). The first spreadsheet contains information regarding each publication (1 publication per row), such as study location, sampling methods. The second spreadsheet contains information about the seabird species studied in each publication (1 row per seabird species per publication). The third spreadsheet contains data for the meta-analysis (1 row per publication, except if the publication studied multiple species, then it would be 1 row per species per publication). - The R code is for the meta-analyses that were undertaken. Comments are included within the code plus detailed information can be found in the Methods section of the paper.

Barrier islands provide resources and ecological services that are integral to economic and environmental interests, such as protection of coastal infrastructure and providing habitat for wildlife. Over time, barrier islands may become eroded and experience land loss, which require management actions to restore island integrity. The process of restoring barrier islands can create new habitats but also alter existing habitats, which can impact the organisms depending on coastal habitats, such as the Endangered Species Act-listed (ESA) Piping Plover (Charadrius melodus) and Red Knot (Calidris canutus). Consequently, we aimed to understand the abundance and behavioral responses from a suite of shorebird species, including American Oystercatcher (Haematopus palliatus), Red Knot, Piping Plover, Snowy Plover (Charadrius nivosus), and Wilson’s Plover (Charadrius wilsonia), to restoration and habitat factors at two restored sites in coastal Louisiana, Whiskey Island and Caminada Headland, from 2012 to 2020. We combined observational data from birds with numerous geospatial predictor variables into a machine learning approach to develop response plots to investigate how birds use coastal habitat with respect to restoration activities at Whiskey Island and Caminada Headland, Louisiana from 2012 to 2020. For each species, we quantified the abundance and behavior (breeding, foraging, leisure) of each individual, which served as response variables in boosted regression tree models, and determined the importance of predictor variables, such as restoration phase, habitat class, inundation class, distance to water, and other remotely or field collected variables from Whiskey Island and Caminada Headland. We ran at least three models for each species, which included non-breeding abundance with a Poisson distribution, foraging behavior with a binomial distribution, and leisure behavior with a binomial distribution. For American Oystercatcher (only occurring in reasonable sample sizes at Whiskey Island) and Wilson’s Plover, we also ran models for breeding abundance with a Poisson distribution and breeding behavior with a binomial distribution.

Barrier islands provide resources and ecological services that are integral to economic and environmental interests, such as protection of coastal infrastructure and providing habitat for wildlife. Over time, barrier islands may become eroded and experience land loss, which require management actions to restore island integrity. The process of restoring barrier islands can create new habitats but also alter existing habitats, which can impact the organisms depending on coastal habitats, such as the Endangered Species Act-listed (ESA) Piping Plover (Charadrius melodus) and Red Knot (Calidris canutus). Consequently, we aimed to understand the abundance and behavioral responses from a suite of shorebird species, including American Oystercatcher (Haematopus palliatus), Red Knot, Piping Plover, Snowy Plover (Charadrius nivosus), and Wilson’s Plover (Charadrius wilsonia), to restoration and habitat factors at two restored sites in coastal Louisiana, Whiskey Island and Caminada Headland, from 2012 to 2020. We combined observational data from birds with numerous geospatial predictor variables into a machine learning approach to develop response plots to investigate how birds use coastal habitat with respect to restoration activities at Whiskey Island and Caminada Headland, Louisiana from 2012 to 2020. For each species, we quantified the abundance and behavior (breeding, foraging, leisure) of each individual, which served as response variables in boosted regression tree models, and determined the importance of predictor variables, such as restoration phase, habitat class, inundation class, distance to water, and other remotely or field collected variables from Whiskey Island and Caminada Headland. We ran at least three models for each species, which included non-breeding abundance with a Poisson distribution, foraging behavior with a binomial distribution, and leisure behavior with a binomial distribution. For American Oystercatcher (only occurring in reasonable sample sizes at Whiskey Island) and Wilson’s Plover, we also ran models for breeding abundance with a Poisson distribution and breeding behavior with a binomial distribution.

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.