Marginal value analysis reveals shifting importance of migration habitat for waterfowl under a changing climate.

Migratory waterfowl are an important resource for consumptive and non-consumptive users alike and provide tremendous economic value in North America. These birds rely on a complex matrix of public and private land for forage and roosting during migration and wintering periods, and substantial conservation effort focuses on increasing the amount and quality of target habitat. Yet, the value of habitat is a function not only of a site's resources but also of its geographic position and weather. To quantify this value, we used a continental-scale energetics-based model of daily dabbling duck movement to assess the marginal value of lands across the contiguous United States during the non-breeding period (September to May). We examined effects of eliminating each habitat node (32 × 32 km) in both a particularly cold and a particularly warm winter, asking which nodes had the largest effect on survival. The marginal value of habitat nodes for migrating dabbling ducks was a function of forage and roosting habitat but, more importantly, of geography (especially latitude and region). Irrespective of weather, nodes in the Southeast, central East Coast, and California made the largest positive contributions to survival. Conversely, nodes in the Midwest, Northeast, Florida, and the Pacific Northwest had consistent negative effects. Effects (positive and negative) of more northerly nodes occurred in late fall or early spring when climate was often severe and was most variable. Importance and effects of many nodes varied considerably between a cold and a warm winter. Much of the Midwest and central Great Plains benefited duck survival in a warm winter, and projected future warming may improve the value of lands in these regions, including many National Wildlife Refuges, for migrating dabbling ducks. Our results highlight the geographic variability in habitat value, as well as shifts that may occur in these values due to climate change.

Effects of weather variation on waterfowl migration: Lessons from a continental-scale generalizable avian movement and energetics model.

We developed a continental energetics-based model of daily mallard (Anas platyrhynchos) movement during the non-breeding period (September to May) to predict year-specific migration and overwinter occurrence. The model approximates movements and stopovers as functions of metabolism and weather, in terms of temperature and frozen precipitation (i.e., snow). The model is a Markov process operating at the population level and is parameterized through a review of literature. We applied the model to 62 years of daily weather data for the non-breeding period. The average proportion of available habitat decreased as weather severity increased, with mortality decreasing as the proportion of available habitat increased. The most commonly used locations during the course of the non-breeding period were generally consistent across years, with the most inter-annual variation present in the overwintering area. Our model revealed that the distribution of mallards on the landscape changed more dramatically when the variation in daily available habitat was greater. The main routes for avian migration in North America were predicted by our simulations: the Atlantic, Mississippi, Central, and Pacific flyways. Our model predicted an average of 77.4% survivorship for the non-breeding period across all years (range = 76.4%-78.4%), with lowest survivorship during autumn (90.5 ± 1.4%), intermediate survivorship in winter (91.8 ± 0.7%), and greatest survivorship in spring (93.6 ± 1.1%). We provide the parameters necessary for exploration within and among other taxa to leverage the generalizability of this migration model to a broader expanse of bird species, and across a range of climate change and land use/land cover change scenarios.

EROD activity, chromosomal damage, and oxidative stress in response to contaminants exposure in tree swallow (Tachycineta bicolor) nestlings from Great Lakes Areas of Concern.

Tree swallow, Tachycineta bicolor, nestlings were collected from 60 sites in the Great Lakes, which included multiple sites within 27 Areas of Concern (AOCs) and six sites not listed as AOCs from 2010 to 2014. Nestlings, approximately 12 days-of-age, were evaluated for ethoxyresorufin-O-dealkylase (EROD) activity, chromosomal damage, and six measures of oxidative stress. Data on each of these biomarkers were divided into four equal numbered groups from the highest to lowest values and the groups were compared to contaminant concentrations using multivariate analysis. Contaminant concentrations, from the same nestlings, included polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), perfluorinated compounds (PFCs), and 17 elements. Alkylated polycyclic aromatic hydrocarbons (aPAHs) and parent PAHs (pPAHs) were measured in pooled nestling dietary samples. Polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans, and pesticides were measured in sibling eggs. Concentrations of aPAHs, pPAHs, chlordane, dieldrin, heptachlor, and PCBs, in that order, were the major contributors to the significant differences between the lowest and highest EROD activities; PFCs, PBDEs, the remaining pesticides, and all elements were of secondary importance. The four categories of chromosomal damage did not separate out well based on the contaminants measured. Concentrations of aPAHs, pPAHs, heptachlor, PCBs, chlordane, and dieldrin were the major contributors to the significant differences between the lowest and highest activities of two oxidative stress measures, total sulfhydryl (TSH) activity and protein bound sulfhydryl (PBSH) activity. The four categories of thiobarbituric acid reacting substances (TBARS), oxidized glutathione (GSSG), reduced glutathione (GSH), and the ratio of GSSG/GSH did not separate well based on the contaminants measured.

A generalizable energetics-based model of avian migration to facilitate continental-scale waterbird conservation.

Conserving migratory birds is made especially difficult because of movement among spatially disparate locations across the annual cycle. In light of challenges presented by the scale and ecology of migratory birds, successful conservation requires integrating objectives, management, and monitoring across scales, from local management units to ecoregional and flyway administrative boundaries. We present an integrated approach using a spatially explicit energetic-based mechanistic bird migration model useful to conservation decision-making across disparate scales and locations. This model moves a Mallard-like bird (Anas platyrhynchos), through spring and fall migration as a function of caloric gains and losses across a continental-scale energy landscape. We predicted with this model that fall migration, where birds moved from breeding to wintering habitat, took a mean of 27.5 d of flight with a mean seasonal survivorship of 90.5% (95% Cl = 89.2%, 91.9%), whereas spring migration took a mean of 23.5 d of flight with mean seasonal survivorship of 93.6% (95% CI = 92.5%, 94.7%). Sensitivity analyses suggested that survival during migration was sensitive to flight speed, flight cost, the amount of energy the animal could carry, and the spatial pattern of energy availability, but generally insensitive to total energy availability per se. Nevertheless, continental patterns in the bird-use days occurred principally in relation to wetland cover and agricultural habitat in the fall. Bird-use days were highest in both spring and fall in the Mississippi Alluvial Valley and along the coast and near-shore environments of South Carolina. Spatial sensitivity analyses suggested that locations nearer to migratory endpoints were less important to survivorship; for instance, removing energy from a 1036 km2 stopover site at a time from the Atlantic Flyway suggested coastal areas between New Jersey and North Carolina, including the Chesapeake Bay and the North Carolina piedmont, are essential locations for efficient migration and increasing survivorship during spring migration but not locations in Ontario and Massachusetts. This sort of spatially explicit information may allow decision-makers to prioritize their conservation actions toward locations most influential to migratory success. Thus, this mechanistic model of avian migration provides a decision-analytic medium integrating the potential consequences of local actions to flyway-scale phenomena.