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Research about Maryland

Source-linked reports with geographic coverage including Maryland.

At least 19 recordsLinked to original sources

Probabilistic forecasting of coastal wetland elevation and soil carbon response to sea-level rise

Tidal wetlands build soil as a dynamic response to inundation, resulting in carbon sequestration and resilience to sea-level rise. Process models can be used to make site-specific forecasts, anticipate future changes, and plan management responses. But to be actionable, forecasts from these models need to be accompanied by descriptions of their confidence. In this study, we demonstrate the application of ecological forecasting principles to the unique case of tidal wetland vulnerability and carbon storage, given accelerating and uncertain sea-level rise. We present a case study using the Cohort Marsh Equilibrium Model at the Global Change Research Wetland in Maryland, USA. We used meta-analyses to quantify lab- and sample-level measurement uncertainties for common soil measurements and to develop Bayesian model priors. Reanalysis of previous literature supported predictive relationships between belowground turnover and mean annual temperature, as well as between soil erodibility and suspended sediment concentration that could be transferable to other locations. The model forecasted a likely conversion of low-elevation marsh to open water by the 2060s, accompanied by a decrease in marsh carbon storage capacity. Forecasted uncertainty in elevation was dominated by structural uncertainty in the model, while carbon accumulation rates were more influenced by parameter uncertainty. After 2050, and increasingly as the forecast approached 2100, uncertainty in sea-level rise projections contributed to uncertainty in both forecasts. Forecasts were most sensitive to processes related to organic matter preservation, plant productivity (maximum aboveground biomass and belowground turnover), and organic soil packing density. The soil formed was an organic-rich peat (>70% organic matter according to the data), and model predictions were insensitive to parameters associated with mineral sedimentation. We identify additional field data collection, such as on decomposition trajectories and plant productivity, and data-model coupling of near-term elevation records as the most impactful strategies for reducing uncertainties in future forecasting efforts. Future work can build on this forecasting framework in other locations, using it for adaptive management, identifying appropriate interventions to mitigate wetland loss, and projecting future carbon removal capacity in response to accelerated sea-level rise.

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An evaluation of transmitter effects on the return rate of adult and juvenile Common Terns to a breeding colony

Advancements in technology have facilitated a rapid expansion in the range of species for which tracking studies can be implemented. Such efforts often require unique attachment methods or materials for which careful evaluation is required to fully understand potential tagging effects and subsequent implications. During the 2021 breeding season, our research team affixed two types of light-weight transmitters to adult and pre-fledgling juvenile Common Terns ( Sterna hirundo ) with leg-loop harnesses made of elastic cord. Our initial observations of these marked birds detected minimal differences in behavior and nesting success of marked adults, and failed to detect any notable impacts on the growth rate or behavior of marked juveniles, but were limited to a single year of data. To provide further insight into the potential effects of these tagging methods, we evaluated return and nesting rates for the 2022 through 2025 breeding seasons. We found that all individuals observed on the breeding grounds in the years following transmitter attachment had not retained the transmitter. The observed tag loss suggest that tag retention could be considered when planning future efforts, and limits our analyses to understanding lagged effects of the unknown duration of actual attachment. With this limitation in mind, we found that birds marked as adults with center-weighted and rear-weighted tags were 1.00 and 0.76 times as likely, respectively, to return to the colony site, and 1.09 and 0.77 times as likely, respectively, to be observed nesting when compared with unmarked controls. Similarly, birds marked as juveniles with rear-weighted transmitters were 0.54 as likely to return, and 0.72 times as likely to nest in subsequent years. These results suggest no negative impacts of center-weighted attachment on return or nesting rates, but moderate support declines in both metrics for birds marked with rear-weighted transmitters.

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3D Elevation Program—Maryland

Using 3D Elevation Program data, a modern illustration of each State's landscape showcases its elevation differences in vivid detail. Each State has been consistently adjusted and colorized according to its highest and lowest elevations, accentuating differences even in States with low relief. To further emphasize landforms, shaded relief has been added on top of the elevation colors.

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The impacts of cover crop biomass on satellite-based detectability of cover crops in Maryland

Cover crop adoption in the U.S. has increased over the past decades, increasing the need to quantify their performance and environmental benefits. While remote sensing (RS)-based approaches for detecting cover crop presence have been developed, there has been limited research on how cover crops with varied biomass and management practices influence detectability. Using unique field-level cover crop presence and biomass datasets in Maryland, U.S., we investigated how RS-based detectability changes for cover crops with varied aboveground biomass, planting, and termination dates. Specifically, we proposed a time-integrated satellite-based greenness feature from Harmonized Landsat-8 and Sentinel-2 (HLS) time series from 2017 to 2021 to estimate biomass of cover crops and evaluated their detectability using a phenology-based cover crop detection framework. The impacts of cover crop planting and termination dates on cover crop biomass were also analyzed. Our results demonstrated that Normalized Difference Vegetation Index (NDVI) estimated biomass with higher accuracy compared to other vegetation indices, and the time-integrated model estimated biomass with higher accuracy than the single-date “snapshot” linear model (R2 from 0.53 to 0.66 and RMSE from 922 kg/ha to 747 kg/ha). While the snapshot models were species sensitive, the time-integrated models showed strong robustness across different species. Detectability increased with cover crop biomass, as detected cover crops averaged 963.3 ±719.5 kg/ha compared to 297.2 ± 209.0 kg/ha for non-detected cover crops. Detection accuracy reached 96.1% for fields exceeding 500 kg/ha, compared with an overall accuracy of 62.7%. Earlier planting and later termination increased biomass and detectability, with biomass rising by 4.14 kg/ha/day (p < 0.01). This study demonstrates how management practices affect cover crop biomass and detectability via satellite time series and provides insights that can inform management of cover crops and monitoring of their effects on agroecosystems.

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Carbon sequestration along a gradient of tidal marsh degradation in response to sea level rise

Tidal marshes are considered one of the world's most efficient ecosystems for belowground organic carbon sequestration and hence climate mitigation. Marsh systems are however also vulnerable to degradation due to climate-induced sea level rise, whereby marsh vegetation conversion to open water often follows distinct spatial patterns: levees (i.e. marsh zones < 10 m from tidal creeks) show lower vulnerability of vegetation conversion to open water than basins (i.e. interior marsh zones > 30 m from creeks). Here, we use sediment cores to investigate spatial variations in organic carbon accumulation rates (OCAR) in a microtidal system (Blackwater marshes, Maryland, USA): (1) across a gradient of marsh zones with increasing marsh degradation, assessed as increasing ratio of unvegetated versus vegetated marsh area and (2) by comparing levees versus basins. We show that OCAR is up to four times higher on marsh levees than in adjacent basins. The data suggest that this is caused by spatial variation in three processes: sediment accretion rate, vegetation productivity, and sediment compaction, which are all higher on levees. Additionally, OCAR was observed to increase with increasing degree of marsh degradation in response to sea level rise. We hypothesize this may be due to more soil waterlogging in more degraded marsh zones, which may decrease carbon decomposition. Our results highlight that tidal marsh levees, in a microtidal system, are among the fastest soil organic carbon sequestration systems on Earth, and that both levees and basins sustain their carbon accumulation rate along gradients of increasing marsh degradation in response to sea level rise.

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Sea-level rise in a coastal marsh: Linking increasing tidal inundation, decreasing soil strength and increasing pond expansion

Coastal marsh conversion into ponds, which may be triggered by sea-level rise, is considered an important driver of marsh loss and their valuable ecosystem services. Previous studies have focused on the role of wind waves in driving the expansion of interior marsh ponds, through lateral erosion of marsh edges surrounding the ponds. Here, we propose another mechanism between sea-level rise, increasing marsh inundation, and decreasing marsh soil strength (approximated here as resistance to shear and penetration stress), that further contributes to marsh erosion and pond expansion. Our field measurements in the Blackwater marshes (Maryland, USA), a microtidal marsh system with organic-rich soils, indicate that (1) an increase in tidal inundation time of the marsh surface above a certain threshold (around 50 % of the time) is associated with a substantial loss of strength of the surficial soils; and (2) this decrease in soil strength is strongly related to the amount of belowground vegetation biomass, which is also found to decrease with increasing tidal inundation at pond bottoms, where the soil has a very low strength. Our finding of decreasing marsh soil strength along a spatial gradient of increasing marsh inundation coincides with a gradient of increasing historical marsh loss by pond expansion, suggesting that feedbacks between sea-level rise, increasing marsh inundation and decreasing marsh soil strength combine to amplify marsh erosion and pond expansion.

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Mapping winter cover crops using remote sensing of crop phenology

Winter cover crops (WCC) are an effective agricultural conservation practice for improving soil health and water quality. Several U.S. states have established incentive programs to promote planting WCC between cash crop rotations. In recent years, the area planted with WCC has steadily increased due to these efforts, although the planting area varies among states. Since these programs are largely led by individual counties or state programs, there is no centralized data repository that quantifies the total WCC planted annually or their locations. Therefore, there is a practical need to identify fields that have been planted with WCC, as well as to quantify the total planted area both during and after the growing season. Furthermore, incentive programs often require verification that WCC were planted to release payments to participating growers in a timely manner. Satellite remote sensing time series can provide information on WCC growth status. However, it remains unclear what kind of WCC the remote sensing data detects. For example, separating WCC from weeds and winter commodity crops remains a challenge. Additionally, a binary classification of WCC presence and absence cannot accurately describe the category and performance of the WCC. This paper presents a new remote sensing phenology-based approach to map WCC likelihood. We assessed model predictions of WCC likelihood using WCC planting records and ground observations over fields at the Beltsville Agricultural Research Center (BARC) from 2018 to 2024. Regional WCC maps were assessed using the Maryland Department of Agriculture's records of WCC fields enrolled in the 2019 and 2020 incentive programs. Our results show that the balanced overall accuracy for WCC and non-WCC ranges from 75% to 85% but could exceed 90%, with limited training samples. However, the high accuracy of WCC corresponds with low accuracy for non-WCC due to confusion with weeds and perennial grasses. Early-season detection yields promising results, with overall accuracies comparable to late-season detection. The after-season detection can differentiate between winter cereal grain cash crops and incentive WCC based on the ending date of the growing season. With a small set of WCC samples and management information, the phenology-based mapping approach offers a rapid and scalable solution for mapping WCC over a large region during or after each WCC growing season.

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Relative activity of three bat species Impacted by white-nose syndrome on the Chesapeake and Ohio Canal National Historical Park

White-nose syndrome, a disease caused by the fungal-pathogen Pseudogymnoascus destructans , has caused drastic reductions in populations of several North American hibernating species of bats including Myotis lucifugus (Little Brown Bat), Myotis septentrionalis (Northern Long-eared Bat), and Perimyotis subflavus (Tricolored Bat). Recent data indicate that populations of Little Brown Bats may be stabilizing and/or increasing in the northeastern region of the US, while others, such as Northern Long-eared Bats, continue to decline. Whether these trends extend to the mid-Atlantic region is currently unknown. To better understand population changes over time, habitat associations, and species dynamics, we developed models of relative activity from bat acoustic data collected on the National Park Service's Chesapeake and Ohio Canal National Historical Park along the Potomac River Corridor in western Maryland between 2016 and 2022. Consistent with pre-disease habitat associations, Little Brown Bats and Tricolored Bats exhibited a positive correlation with proximity to water bodies. Notably, we found Little Brown Bat and Tricolored Bat populations potentially were increasing, whereas Northern Long-eared Bats showed no correlation with examined habitat covariates and had low detection levels, trends consistent with broader declines throughout their range.

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Assessing the topographic distribution of legacy soil phosphorus in agricultural fields of the Delmarva Peninsula, Mid-Atlantic Coastal Plain, USA

Phosphorus (P) management remains a challenge in agricultural watersheds. The Choptank River Conservation Effects Assessment Project watershed, located in Maryland and Delaware and draining to the Chesapeake Bay, contains legacy soil P from historical dairy and poultry manure applications. These practices elevated soil P beyond crop needs, contributing to persistent P export to aquatic ecosystems. We assessed spatial P distribution and analyzed GIS (Geographic Information Systems)-derived landscape features driving legacy P movement on a farm (47 ha). We hypothesized that P accumulates in drained lowlands and depressional areas due to gravity-driven processes that accelerate P-enriched water to receiving waters via overland flow. In collaboration with the US Department of Agriculture Legacy P project, we collected 105 soil samples (0- to 5-cm and 5- to 15-cm depths) and 14 ditch sediment samples across five topographic openness classes from a farm with >100 years of dairy manure application. Average Mehlich-III P concentrations were 218 and 179 mg kg −1 at 0- to 5-cm and 5- to 15-cm depths, respectively, with legacy areas defined by P content > 100 mg kg −1 . Soil P and clay particle size were positively correlated ( r = 0.42, p < 0.05), increased as landscape openness decreased, and were negatively correlated with topographic openness (ranging from −0.2 to −0.4, p < 0.05), indicating accumulation of P and clay in low-lying areas. These patterns suggest that historical field-level managements have primarily shaped P distribution, while hydrologic and landscape properties further influence its redistribution via transport pathways and drainage. These findings support the development of landscape models to map critical source areas in low-relief watersheds and guide targeted mitigation in high-risk P export zones.

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Satellite assessment of winter cover crop and conservation tillage outcomes to support adaptive management in working landscapes

The use of winter cover crops and conservation tillage are agricultural practices promoted to reduce nutrient and sediment loss from cropland, improve soil health, increase infiltration, and support farm nutrient cycling and ecosystem services. However, environmental performance of these practices is variable in the working farm landscape. The Lower Chesapeake Bay research project within the USDA Long-Term Agroecosystem Research (LTAR) network has collaboratively developed satellite remote sensing algorithms to measure the performance and phenology of winter cover crops (aboveground biomass, nitrogen content, fractional cover, and emergence and termination dates) using no-cost Harmonized Landsat and Sentinel-2 multispectral satellite imagery. This research supports annual operational assessment of >28,000 fields per year in four states. Results document the impacts of agronomic management on conservation outcomes, support adaptive management of incentive payment structures, and can reduce the workload for conservation district staff by remotely verifying cover crop management. Additionally, super-spectral satellite applications have been developed to accurately map crop residue cover by measuring lignocellulose absorption in shortwave infrared wavelengths, producing a 7-year time series of tillage intensity maps for the Delmarva Peninsula. These remote sensing products can be used in decision support and modeling to estimate changes in nutrient, sediment, and carbon cycling resulting from conservation practice implementation in the working farm landscape. This manuscript provides an overview of remote sensing research findings and applications associated with the USDA LTAR and Conservation Effects Assessment Projects (CEAP), documenting a variety of previously published outcomes with update and expansion of techniques using additional unpublished data and analyses as appropriate.

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Multi-model comparison of salt marsh longevity under relative sea-level rise

Understanding salt marsh resilience under increasing sea levels can inform for management decisions. We compared temporal projections from various wetland process-based models and a geospatially derived metric (i.e., marsh lifespan) to understand key considerations and uncertainties about salt marsh resilience when using these products for decision-making. The influences of lidar topographic correction and marsh surface sediment accretion were explored across a suite of relative sea level rise (RSLR) projections to assess differences in the timing and amount of habitat change for each modeling approach. All models were run for a small coastal wetland site located in the Chesapeake Bay, Maryland, USA, to assess potential change in marsh habitat, and timing of marsh loss due to RSLR. All modeling results agreed that marsh longevity was threatened by RSLR but they varied in the time of predicted marsh submergence between the years 2070 and 2100 depending on the initial marsh surface elevation and accretion rates. Models with similar accretion rates predicted similar years until marsh submergence. Removing a positive elevation bias from lidar surveys in densely vegetated marsh areas for these models resulted in onset of submergence ~ 7 years earlier. Because there are many tradeoffs to each model type, end users need to evaluate management questions, overall goals, the amount of effort involved in model parameterization, and the amount of uncertainty in the model that they are willing to accept.

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Experimental evaluation of Eastern box turtle (Terrapene carolina carolina) detectability in visual search surveys

Understanding how detection probability varies over time, space, or in response to measurable covariates is important to inform the monitoring and assessment of many species. A standard model to understand detectability, the availability/perception model, admits that detection probability is the composite of two components: availability and ability of surveyors to detect the target. Availability is largely affected by environmental and behavioral factors, whereas perception is primarily affected by attributes of individual observers and survey protocols, and thus can potentially be partially controlled by survey design. We designed and implemented a field study to understand the perception component of detection for Eastern Box Turtles ( Terrapene carolina carolina ) using visual encounter surveys. We obtained and deployed museum specimens of Eastern Box Turtle shells and subjected them to visual search surveys by observers in realistic field situations. Overall, about 50% of the box turtle shells were detected by observers, including 41.5% in what we categorized as partially visible and 63.0% as fully visible. There were significant differences among observers, which may be due to observer-specific variation in search technique; the observers varied in how well they achieved the protocol guidance. Therefore, in visual search surveys, care in study design and analysis should be taken to account for variation in perception to determine detectability, as our study suggests 37% of perceptible targets are missed by surveyors.

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Multispectral red-edge indices accurately estimate nitrogen content in winter cereal cover crops

Winter cover crops reduce erosion and nutrient runoff from agricultural systems. Although cereal cover crops can decrease field nitrate leaching by 50%–95%, the magnitude of this reduction varies within and between fields, making it challenging to monitor the impact of cover crops on nitrate leaching at large spatial extents. Satellite remote sensing using red-edge bands has been shown to effectively estimate crop nitrogen (N) content (kg ha −1 ) in later growth-stage crops with a closed canopy. In this study, we evaluated 15 spectral indices derived from Sentinel-2 imagery to estimate N concentration (%) and content (kg ha −1 ) of cereal cover crops, using 1627 destructive samples collected from 2018 to 2023 in Maryland. Observed N content ranged from 0.1 to 214.7 kg ha −1 , while N concentration ranged from 0.6% to 5.5%. The 15 indices considered were poor predictors of N concentration (adj. R 2 = 0.089, root mean squared error [RMSE] = 0.802%), but were more successful at measuring N content (biomass × N concentration). Delta red-edge (ΔRE) was the best predictor of N content (adj. R 2 = 0.748, RMSE = 13.10 kg ha −1 from cross-validation with 80% train and 20% test splits iterated 100 times) using samples with imagery collected within ±4 days of destructive sampling ( n = 1110). Our findings indicate that longer red-edge wavelengths (783 and 740 nm) are more suited for estimating N content in cereal cover crops compared to shorter red-edge wavelengths, which have been shown to be more sensitive to biomass. Leave-one-year-out cross-validation demonstrated that the relationship between ΔRE and N content was robust across all four cover crop sampling years included in the study (adj. R 2 = 0.700–0.769, RMSE = 10.70–15.40 kg ha −1 ). Regression model performance improved with the addition of multiple predictors, including biomass (estimated from Normalized Difference Vegetation Index), weather variables (adj. R 2 = 0.765, RMSE = 12.37 kg ha −1 ), management variables (species, season, adj. R 2 = 0.772, and RMSE = 12.13 kg ha −1 ), and biophysical variables (height, fractional ground cover, adj. R 2 = 0.818, and RMSE = 10.29 kg ha −1 ). These findings demonstrate the feasibility of quantifying N content in cereal cover crops using a red-edge-based spectral index across large geographic extents and indicate the inclusion of additional predictors, such as weather and management data, improves model accuracy. This work has implications for quantifying reductions in N leaching associated with cover crops, aiding in policymaking and evaluation of conservation programs that impact water bodies such as Chesapeake Bay.

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Hidden legacies: Investigating buried pre-colonial stream corridors in the Mid-Atlantic Coastal Plain, Maryland, USA

Within the Mid-Atlantic United States, widespread landscape disturbance during European colonization resulted in erosion and subsequent storage of legacy sediments within river valleys and floodplains, altering their form, function, and flora. Previous studies of precolonial river corridors have influenced river restoration designs and targets throughout the region, but the generalizability of these studies into other physiographic settings, such as the Coastal Plain, is unknown. Therefore, our study investigated the physical form and riparian vegetation of pre-colonial stream corridors located within the Coastal Plain of Anne Arundel County, Maryland, documenting changes from pre- to colonial and postcolonial time periods. Our study provides evidence of buried, precolonial riparian ecosystems with dates ranging between 750 years to 8000 years Before Present. These valley bottom ecosystems were likely a dynamic patch mosaic, largely dominated by dense Alnus (alder) scrub swamps with variable Poaceae (grass) and Cyperaceae (sedge) dominated meadows and both multi-threaded and single-threaded channel forms. These precolonial floodplains are buried by vast amounts of legacy sediment to the extent that pre-colonial sediments are largely not exposed in the modern valley bottom. Notably, the Coastal Plain precolonial corridors investigated in this study contrast to studies in the Piedmont physiographic region with precolonial sediments exposed in streambanks and with precolonial ecosystems described as herbaceous stream-wetlands. Our findings provide critical historical context as to the magnitude of alteration for modern stream channels and suggest an alternative precolonial ecosystem which can be used to inform restoration designs, management targets, and reestablishment of channel functional processes in areas of the Mid-Atlantic Coastal Plain.

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Contaminated stormwater sediment source tracking for polychlorinated biphenyls in an urban watershed of the Chesapeake Bay, United States

Fine-grained sediment in stormwater acts as a vector for persistent organic pollutants, like polychlorinated biphenyls (PCBs), through mobilization from sources within drainage areas of impacted urban watersheds. This study implemented a novel approach to identify the relative contributions of various landscape and stream sources of sediment from the Back River watershed in eastern Baltimore, Maryland, and investigated the applicability of using trace PCBs found in an urban environment as discriminants between each source type. Trace PCBs were found to be poor discriminants when identifying the relative sediment contributions of watershed-scale land use categories. When excluding PCBs in the development of a sediment fingerprinting model and instead utilizing trace elements and carbon only, sediment fingerprint modeling successfully differentiated green spaces and eroding streambanks as the most significant contributors to stormwaters sediment (37.1 % and 44.0 %, respectively) of the total sediment contributions of all considered source categories. In all samples collected from various landscape sources, storms, and cores detectable concentrations of PCBs were measured. The results of this study indicate that sediment fingerprinting may not be an effective method in predicting where PCBs may be found within an impacted watershed.

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Comparative assessment of a restored and natural wetland using 13C-DNA SIP reveals a higher potential for methane production in the restored wetland

Wetlands are the largest natural source of methane (CH 4 ), a potent greenhouse gas produced by methanogens. Methanogenesis rates are controlled by environmental factors such as redox potential, temperature, and carbon and electron acceptor availability and are presumably dependent on the composition of the active methanogen community. We collected intact soil cores from a restored and natural freshwater depressional wetland on Maryland’s Delmarva Peninsula (USA) to assess the effects of wetland restoration and redox shifts on microbial processes. Intact soil cores were incubated under either saturated (anoxic) or unsaturated (oxic) conditions and amended with 13 C-acetate for quantitative stable isotope probing (qSIP) of the 16S rRNA gene. Restored wetland cores supported a distinct community of methanogens compared to natural cores, and acetoclastic methanogens putatively identified in the genus Methanosarcina were among the most abundant taxa in restored anoxic and oxic cores. The active microbial communities in the restored wetland cores were also distinguished by the unique presence of facultatively anaerobic bacteria belonging to the orders Firmicutes and Bacteroidetes . In natural wetland incubations, methanogen populations were not among the most abundant taxa, and these communities were instead distinguished by the unique presence of aerobic bacteria in the phyla Acidobacteria , Actinobacteria , and class Alphaproteobacteria . Iron-reducing bacteria, in the genus Geobacter , were active across all redox conditions in both the restored and the natural cores, except the natural oxic–anoxic condition. These findings suggest an overall higher potential for methanogenesis in the restored wetland site compared to the natural wetland site, even when there is evidence of Fe reduction.

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Avian influenza infection and antibodies not identified in eastern wild turkeys (Meleagris gallopavo silvestris) sampled on the Delmarva Peninsula

Although highly pathogenic avian influenza presents a notable threat to domestic turkeys ( Meleagris gallopavo domesticus ), there have been minimal infections identified in wild turkeys ( Meleagris gallopavo ) across the United States. Indeed, recent infections in wild turkeys have either been linked back to or suspected to be the result of spillback from nearby infected domestic turkeys. This study presents avian influenza sampling data for Eastern wild turkeys ( Meleagris gallopavo silvestris ) across the Maryland portion of the Delmarva Peninsula, in the winter of 2023–2024, with an objective of identifying any circulating influenza A viruses (IAVs), as well as determining the extent of previous exposure to IAVs in this population. We collected swab samples from 36 female wild turkeys. No IAV viral RNA was detected in any sample, based on real-time reverse transcriptase PCR. We collected sera from 31 of the 36 sampled individuals, all of which had biomimetic enzyme-linked immunosorbent assay (bELISA) S/N values >0.7 (range: 0.79–1.29) indicating a lack of antibodies to IAVs. Although our sample size is limited, these results indicate no evidence of current or recent previous IAV infection in sampled birds.

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Common Terns (Sterna hirundo) use of a staging site in the Chesapeake Bay

In 2021, we initiated fieldwork to assess the relative importance of a staging area for Sterna hirundo (Common Tern) at a pier at the confluence of the Patuxent River and Chesapeake Bay, MD. During the post-breeding periods of 2021 through 2023, we resighted 378 banded Common Terns at this staging area, with individuals originating from 6 breeding colonies. Most banded individuals were from Poplar Island, a major nesting site 50 km north of the pier, with up to 37% of that island's annual hatch-year population observed at this staging area. Additionally, biologists have previously observed staging terns at this site, suggesting these observations do not reflect a change in the species' behavior within the region. Cumulatively, our data suggest that this habitat acts as an important staging area for the Chesapeake Bay's Common Tern population, particularly for those nesting on Poplar Island.

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