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Conserving tidal‐marsh bird communities requires strategies to address continuing pressures from human development to the effects of increasing rates of sea‐level rise. Knowing tidal‐marsh bird distributions and population sizes are important for developing these strategies. In the Northeast United States, where estimates of sea‐level rise are 3 times higher than the global average, 5 bird species are tidal‐marsh specialists: clapper rail (Rallus crepitans), willet (Tringa semipalmata), Nelson's sparrow (Ammospiza nelsoni), saltmarsh sparrow (A. caudacuta), and seaside sparrow (A. maritima). We used a regional marsh bird survey to develop Bayesian network models to identify factors that influence patch‐scale species density and to estimate regional population sizes. We modeled species density as a function of habitat covariates at the patch, local, landscape, and regional spatial scales. Densities were most sensitive to patch location and dimension, patch geomorphic setting, indices of human development, and changes in mean sea level. We estimated 110,000 clapper rails (95% CI = 61,000–159,000), 111,000 willets (95% CI = 70,000–152,000), 7,000 Nelson's sparrows (95% CI = 4,000–10,000), 60,000 saltmarsh sparrows (95% CI = 40,000–80,000), and 234,000 seaside sparrows (95% CI = 112,000–356,000) from the United States–Canada border to, and including, the mouth of the Chesapeake Bay, Virginia, USA. Our abundance estimates can be used to identify priority conservation areas at multiple geographic scales and our models help identify key habitat and landscape components for tidal‐marsh restoration and management to benefit tidal‐marsh birds and can be modified for other species. © 2018 The Wildlife Society. Our Bayesian models help identify marsh patches that support breeding tidal‐marsh specialist birds in the Northeast United States and provide information that helps focus conservation actions to maintain tidal‐marsh bird communities. Our results support conserving patches with lower rates of sea‐level rise and prioritizing tidal‐marsh restoration and management techniques that maintain suitable habitat for nesting tidal‐marsh birds. [ABSTRACT FROM AUTHOR]

Few biogeographic studies of dinoflagellate cysts include the near-shore estuarine environment. We determine the effect of estuary type, biogeography, and water quality on the spatial distribution of organic-walled dinoflagellate cysts from the Northeast USA (Maine to Delaware) and Canada (Prince Edward Island). A total of 69 surface sediment samples were collected from 27 estuaries, from sites with surface salinities >20. Dinoflagellate cysts were examined microscopically and compared to environmental parameters using multivariate ordination techniques. The spatial distribution of cyst taxa reflects biogeographic provinces established by other marine organisms, with Cape Cod separating the northern Acadian Province from the southern Virginian Province. Species such as Lingulodinium machaerophorum and Polysphaeridinium zoharyi were found almost exclusively in the Virginian Province, while others such as Dubridinium spp. and Islandinium? cezare were more abundant in the Acadian Province. Tidal range, sea surface temperature ( SST), and sea surface salinity ( SSS) are statistically significant parameters influencing cyst assemblages. Samples from the same type of estuary cluster together in canonical correspondence analysis when the estuaries are within the same biogeographic province. The large geographic extent of this study, encompassing four main estuary types (riverine, lagoon, coastal embayment, and fjord), allowed us to determine that the type of estuary has an important influence on cyst assemblages. Due to greater seasonal variations in SSTs and SSSs in estuaries compared to the open ocean, cyst assemblages show distinct latitudinal trends. The estuarine context is important for understanding present-day species distribution, the factors controlling them, and to better predict how they may change in the future. [ABSTRACT FROM AUTHOR]

Over two million hectares of marginal land in the Northeast USA no longer used for agriculture may be suitable and available for production of second-generation cellulosic bioenergy crops, offering the potential for increased regional bioenergy production without competing with food production on prime farmland. Current yields of perennial bioenergy grasses and short-rotation woody crops range from 2.3 to 17.4 and 4.5 to 15.5 Mg/ha, respectively, and there is great potential for increased yields. Regional advantages for bioenergy development include abundant water resources, close proximity between production and markets, and compatibility of bioenergy cropping systems with existing agriculture. As New York and New England (a subset of the Northeast region) account for ~85 % of the nation's heating oil consumption, production of bioheat, biopower, and combined heat and power could substantially reduce the region's dependence on imported petroleum. While numerous grassroots efforts are underway in the region across supply chains, bioenergy development faces several challenges and unknowns in terms of environmental impact, production, yields, socioeconomics, and policy. We explore the opportunities for second-generation bioenergy production on the unused marginal lands of the Northeast USA and discuss the challenges to be addressed to promote sustainable bioenergy production on the region's underutilized marginal land base. [ABSTRACT FROM AUTHOR]

The article presents a case study which evaluates the effectiveness of the duplex assay method developed by researchers of the University of Connecticut in the investigation of the phocine distemper virus (PDV). Topics discussed include the use of tissue samples from various seal species for the evaluation of the duplex assay method, the comparison of the duplex assay method with the singleplex assay method in terms of precision and specificity, and a detailed analysis of the results.

This analysis of Northeast US federal fisheries management focused on how social data have been collected and incorporated. Qualitative analysis of semi-structured interviews with 45 primary informants was augmented with secondary data. Results showed that the social factors of Northeast US federal fisheries are considered important, and that participation in and processes involved with collecting and incorporating social data have improved over time. Nonetheless, progress is still necessary to ensure that managers have the information necessary to understand how fishermen and fishing communities might be impacted by decisions. Managers tend rely on perception and public comment, rather than social impact assessment (SIA) documents. A number of steps are being taken to improve data collection, analysis, and use. Similar challenges exist nation-wide, but dialogue among providers of SIAs is elevating the quality and consistency of products. Where social scientists are engaged early and consistently, fostering the consideration of human dimensions in the design of measures in a participatory and iterative manner, both the SIA process and product are most valuable. [ABSTRACT FROM PUBLISHER]

Water depth is an important environmental variable that explains a significant portion of the variation in the chironomid fauna of shallow lakes. We developed site-specific and local chironomid water-depth inference models using 26 and 104 surface-sediment samples, respectively, from seven kettlehole lakes in the Plymouth Aquifer, southeast Massachusetts, USA. Our site-specific model spans a depth gradient of 5.6 m, has an $$ {\text{r}}_{\text{jack}}^{2} $$ of 0.90, root mean square error of prediction (RMSEP) of 0.5 m and maximum bias of 0.7 m. Our local model has a depth gradient of 11.7 m, an $$ {\text{r}}_{\text{jack}}^{2} $$ of 0.71, RMSEP of 1.6 m and maximum bias of 2.9 m. Principal coordinates of neighbourhood matrices (PCNM) analysis showed that there is no influence of spatial autocorrelation on the site-specific model, but PCNM variables explained a significant amount of variance (4.8%) in the local model. This variance, however, is unique from the variance explained by water depth. We applied the inference models to a Holocene chironomid record from Crooked Pond, a site for which multiple, independent palaeohydrological reconstructions are available. The chironomid-based reconstructions are remarkably similar and show stable water depths of ~5 m, interrupted by a 2-m decrease between 4,200 and 3,200 cal a BP. Sedimentological evidence of water level fluctuations at Crooked Pond, obtained using the so-called Digerfeldt approach, also shows a drop in water depths around that time. The period of reconstructed lower water levels coincides with the abrupt decline in moisture-dependent hemlock in this region, providing further evidence for this major palaeohydrological event. The site-specific model has the best performance statistics, but the high percent abundance of fossil taxa from the long core that are absent or rare in the training set makes the site-specific reconstruction unreliable for the period before 4,400 cal a BP. The fossil taxa are well represented in the local model, making it the preferred inference model. The strong similarity between the chironomid-based reconstructions and the independent palaeohydrological records highlights the potential for using chironomid-based inference models to determine past lake depths at sites where temperature was not an influencing factor. [ABSTRACT FROM AUTHOR]

An air quality modeling system was used to simulate the effects on ozone concentration in the northeast USA from climate changes projected through the end of the twenty-first century by the National Center for Atmospheric Research's (NCAR's) parallel climate model, a fully coupled general circulation model, under a higher and a lower scenario of future global changes in concentrations of radiatively active constituents. The air quality calculations were done with both a global chemistry-transport model and a regional air quality model focused on the northeast USA. The air quality simulations assumed no changes in regional anthropogenic emissions of the chemical species primarily involved in the chemical reactions of ozone creation and destruction, but only accounted for changes in the climate. Together, these idealized global and regional model simulations provide insights into the contribution of possible future climate changes on ozone. Over the coming century, summer climate is projected to be warmer and less cloudy for the northeast USA. These changes are considerably larger under the higher scenario as compared with the lower. Higher temperatures also increase biogenic emissions. Bothmean daily and 8-h maximum ozone increase from the combination of three factors that tend to favor higher concentrations: (1) higher temperatures change the rates of reactions and photolysis rates important to the ozone chemistry; (2) lower cloudiness (higher solar radiation) increases the photolysis reaction rates; and (3) higher biogenic emissions increase the concentration of reactive species. Regional model simulations with two cumulus parameterizations produce ozone concentration changes that differ by approximately 10%, indicating that there is considerable uncertainty in the magnitude of changes due to uncertainties in how physical processes should be parameterized in the models. However, the overall effect of the climate changes simulated by these models - in the absence of reductions in regional anthropogenic emissions - would be to increase ozone concentrations. [ABSTRACT FROM AUTHOR]

• Contemporary rates of forest disturbance are high in the northern Acadian Forest. • Aboveground biomass dynamics and timber harvesting were simulated using LANDIS-II. • Projected rates of species turnover were high, 2010–2060, under recent harvest rates. • Co-occurrence patterns likely to shift, destabilizing regional forest types. • Local logging effects on species abundance key to modeling working forest resilience. Preventing declines of native and historically-abundant tree species is an important aspect of sustainable forest management, but predicting future forest composition is challenging when succession does not tend to follow a well-defined path. We evaluated the implications of site-level interactions between timber harvesting and forest succession on the regional landscape dynamics of the complex and species-rich northern Acadian Forest Region. Our expectation was that forest composition would trend away from long-lived and shade-tolerant species, because rates of landscape disturbance from timber harvesting are high relative to historic rates of natural disturbance. We used a novel modeling approach that combined Landsat-derived time series of forest disturbance to inform realistic simulations of timber harvesting across many individual commercial forest landowners using LANDIS-II, and evaluated changes in tree species' distributions and abundance with and without harvesting. Detailed descriptions of initial forest conditions were derived from maps of relative tree species abundance, developed using Landsat satellite imagery, regional inventory data, and an innovative machine learning algorithm. If recent harvest rates persist, simulations suggest timber harvesting will generally be sustainable in our study area; however, projected rates of site-level species turnover were high, predominantly favoring species that were less abundant under the region's natural disturbance regime. As a result, broad-scale patterns of projected species co-occurrence shifted, destabilizing important regional forest types. Our results highlight both the region's capacity for forest growth and the importance of accurately capturing the local effects of land management when projecting forested regions dominated by commercial ownership. [ABSTRACT FROM AUTHOR]

The electricity sector is dependent on rivers to provide ecosystem services that help regulate excess heat, either through provision of water for evaporative cooling or by conveying, diluting and attenuating waste heat inputs. Reliance on these ecosystem services alters flow and temperature regimes, which impact fish habitat and other aquatic ecosystem services. We demonstrate the contemporary (2000–2010) dependence of the electricity sector on riverine ecosystem services and associated aquatic impacts in the Northeast US, a region with a high density of thermoelectric power plants. We quantify these dynamics using a spatially distributed hydrology and water temperature model (the framework for aquatic modeling in the Earth system), coupled with the thermoelectric power and thermal pollution model. We find that 28.4% of thermoelectric heat production is transferred to rivers, whereas 25.9% is directed to vertical cooling towers. Regionally, only 11.3% of heat transferred to rivers is dissipated to the atmosphere and the rest is delivered to coasts, in part due to the distribution of power plants within the river system. Impacts to the flow regime are minimal, while impacts to the thermal regime include increased river lengths of unsuitable habitats for fish with maximum thermal tolerances of 24.0, 29.0, and 34.0 ° C in segments downstream of plants by 0.6%, 9.8%, and 53.9%, respectively. Our analysis highlights the interactions among electricity production, cooling technologies, aquatic impacts, and ecosystem services, and can be used to assess the full costs and tradeoffs of electricity production at regional scales.

• Forest composition likely to shift in the Northeast, USA over the next 200 years. • Sugar maple and American beech will likely remain dominant in study area. • Eastern hemlock and red spruce likely to experience reductions in relative biomass. • Successional dynamics projected to drive forest composition over the next century. • Projected climate change to influence composition over the next two centuries. • Managers may need to increase application of adaptive strategies. Global change represents the greatest challenge facing forest managers today. The uncertainty and variability of potential future impacts of shifting climatic and disturbance regimes has led resource managers to seek out alternative approaches to sustain the long-term delivery of forest ecosystem services. We use a spatially explicit forest landscape simulation model, LANDIS-II, to examine and evaluate a range of long-term effects of current and adaptive forest management under three projected climate scenarios within a forested landscape in southeastern Vermont, USA. We found that land-use legacies and the inertia associated with long-term forest successional trajectories are likely to be the dominant driver of future forest composition and biomass conditions for the next 100 years. Nevertheless, climate is projected to have a greater influence on species composition and aboveground biomass over the next 200 years. Eastern hemlock (Tsuga canadensis) and red spruce (Picea rubens) are likely to experience reductions in aboveground biomass and a compression of relative dominance on the landscape. American beech (Fagus grandifolia) and sugar maple (Acer saccharum) are projected to persist within the landscape and are likely to continue to occupy a prominent compositional position in the forests of this region. Extreme climate warming under RCP 8.5 projections resulted in compositional shifts and reductions in landscape-scale aboveground biomass (120.09 ± 4.51 M g · h a - 1 ) at the end of the 200 year simulation when compared to RCP 4.5 (150.55 ± 1.04 M g · h a - 1 ) and current climate projections (147.90 ± 0.79 M g · h a - 1 ). These findings highlight the expected lag effects of a changing climate, which present significant challenges and opportunities as managers seek to sustain critical ecosystem services in the region. [ABSTRACT FROM AUTHOR]