Managers need to predict how animals will respond to habitat redistributions caused by climate change. Our objective was to model the effects of sea level rise on total eelgrass (Zostera marina) habitat area and on the amount of that area that is accessible to Brant geese (Branta bernicla), specialist grazers of eelgrass. Digital elevation models were developed for seven estuaries from Alaska, Washington, California (USA), and Mexico. Scenarios of future total eelgrass area were derived from combinations of estuarine specific sediment and tectonic rates (i.e., bottom change rate) with three rates of eustatic sea level rise (ESLR). Percentages of total eelgrass areas that were accessible to foraging Brant were determined for December when the birds overwinter at more southerly sites and in April as they move north to sites where they build body stores on their way to nesting areas in Alaska. The modeling showed that accessible eelgrass area could be lower than total area due to how daytime low-tide height, eelgrass shoot length, and the upper elevation of eelgrass determined Brant-reaching depth. Projections of future eelgrass area indicated that present-day ESLR (2.8 mm/yr) and bottom change rates should sustain the current pattern of estuarine use by Brant except in Morro Bay, where use should decrease because eelgrass is being ejected from this estuary by a positive bottom change rate. Higher ESLR rates (6.3 and 12.7 mm/yr) should result in less Brant use of estuaries at the northern and southern ends of the flyway, particularly during the winter, but more use of mid-latitude estuaries. The capacity of midlatitude estuaries to function as Brant feeding refugia, or for these estuaries and Izembek Lagoon to provide drift rather than attached leaves, is eventually limited by the decrease in total eelgrass area, which is a result of a light extinction affect on the eelgrass, or the habitat being pushed out of the estuary by positive tectonic rates. Management responses are limited to the increase or decrease of sediment supply and the relocation of levees to allow for upslope migration of eelgrass habitat.
Changes in climate, food abundance and disturbance from humans threaten the ability of species to successfully use stopover sites and migrate between non‐breeding and breeding areas. To devise successful conservation strategies for migratory species we need to be able to predict how such changes will affect both individuals and populations. Such predictions should ideally be process‐based, focusing on the mechanisms through which changes alter individual physiological state and behavior. In this study we use a process‐based model to evaluate how Black Brant (Branta bernicla nigricans) foraging on common eelgrass (Zostera marina) at a stopover site (Humboldt Bay, USA), may be affected by changes in sea level, food abundance and disturbance. The model is individual‐based, with empirically based parameters, and incorporates the immigration of birds into the site, tidal changes in availability of eelgrass, seasonal and depth‐related changes in eelgrass biomass, foraging behavior and energetics of the birds, and their mass‐dependent decisions to emigrate. The model is validated by comparing predictions to observations across a range of system properties including the time birds spent foraging, probability of birds emigrating, mean stopover duration, peak bird numbers, rates of mass gain and distribution of birds within the site: all 11 predictions were within 35% of the observed value, and 8 within 20%. The model predicted that the eelgrass within the site could potentially support up to five times as many birds as currently use the site. Future predictions indicated that the rate of mass gain and mean stopover duration were relatively insensitive to sea level rise over the next 100 years, primarily because eelgrass habitat could redistribute shoreward into intertidal mudflats within the site to compensate for higher sea levels. In contrast, the rate of mass gain and mean stopover duration were sensitive to changes in total eelgrass biomass and the percentage of time for which birds were disturbed. We discuss the consequences of these predictions for Black Brant conservation. A wide range of migratory species responses are expected in response to environmental change. Process‐based models are potential tools to predict such responses and understand the mechanisms which underpin them.
Climate change is driving worldwide shifts in the distribution of biodiversity, and fundamental changes to global avian migrations. Some arctic-nesting species may shorten their migration distance as warmer temperatures allow them to winter closer to their high-latitude breeding grounds. However, such decisions are not without risks, since this intensifies pressure on resources when they are used for greater periods of time. In this study, we used an individual-based model to predict how future changes in food abundance, winter ice coverage, and human disturbance could impact an Arctic/sub-Arctic breeding goose species, black brant (Branta bernicla nigricans, Lawrence 1846), and their primary food source, common eelgrass (Zostera marina L.), at the Izembek Lagoon complex in southwest Alaska. Brant use the site during fall and spring migrations, and increasingly, for the duration of winter. The model was validated by comparing predictions to empirical observations of proportion of geese surviving, proportion of geese emigrating, mean duration of stay, mean rate of mass gain/loss, percentage of time spent feeding, number of bird days, peak population numbers, and distribution across the complex. The model predicted that reductions >50% of the current decadal (2007-2015) mean of eelgrass biomass, which have been observed in some years, or increases in the number of brant, could lead to a reduction in the proportion of birds that successfully migrate to their breeding grounds from the site. The model also predicted that access to eelgrass in lagoons other than Izembek was critical for overwinter survival and spring migration of brant, if overall eelgrass biomass was 50% of the decadal mean biomass. Geese were typically predicted to be more vulnerable to environmental change during winter and spring, when eelgrass biomass is lower, and thermoregulatory costs for the geese are higher than in fall. We discuss the consequences of these predictions for goose population trends in the face of natural and human drivers of change.
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