Sea-level rise impacts on migratory flyways in the eastern Pacific
Research Background
Millions of shorebirds migrate annually from their Russian and Alaskan Arctic breeding habitats to the coasts of Southeast Asia and Australasia through the East Asian–Australasian Flyway (EAAF). These birds interrupt their journeys to rest and feed in intertidal habitats at staging sites across eastern Asia that can constitute significant bottlenecks for migration. For example, over 45 per cent of all red knots Calidris canutus in the flyway use a single site in the Yellow Sea during their migration. Habitat loss from sea-level rise (SLR) at such bottleneck sites could disproportionately impact population persistence, but to our knowledge, the magnitude of these effects has not been quantified in this or any other migration system. Here, we estimate the vulnerability of migratory routes for shorebirds to future loss of coastal habitat through SLR across all the EAAF sites used by the birds.
Research Objectives
To guide conservation investment that minimizes losses of migratory bird populations during migration, we developed a spatially explicit flyway model coupled with a maximum flow algorithm. Migratory routes of 10 shorebird taxa were modeled in a graph theoretic framework by representing clusters of important wetlands as nodes and the number of birds flying between 2 nodes as edges. We also evaluated several resource allocation algorithms that required only partial information on flyway connectivity (node strategy, based on the impacts of SLR at nodes; habitat strategy, based on habitat change at sites; population strategy, based on population change at sites; and random investment).
To model the impacts of habitat loss on the migratory shorebird populations, we estimate the flow of birds through the network of habitat patches by applying an algorithm widely used to solve the maximum flow problem, developed to calculate the maximum amount of flow running through complex networks (e.g. water in a pipeline system). There is growing interest in applying graph theory to ecological phenomena, though its application has so far been limited to analyses of network structure such as metapopulations and landscape connectivity. Using our novel application of graph theory, we estimate the impact of habitat loss on the maximum flow capacity of migratory populations (hereafter referred to as ‘population flow’) of 10 migratory shorebird taxa using the EAAF. Migratory pathways are modelled using a graph consisting of nodes connected by edges representing the flow of individuals along the migration route (see figure 1 and electronic supplementary material). We applied an algorithm quantifying the maximum flow that the network could support, given any particular configuration of habitat availability across the nodes.
Results
Without any conservation investment, average population flow for all 10 taxa dropped to 82% at 50 cm SLR and to 10% at 300 cm SLR. Investment to protect upshore habitat resulted in the retention of much larger population flows for any given SLR scenario, though the magnitude of this improvement varied markedly among investment strategies. Random investment produced the poorest results; there was a roughly linear increase in retained population flow as investment increased. The other strategies performed as expected; retention of population flow increased as use of information about migratory connectivity increased for a given budget.
Spatial investment patterns of the flyway strategy aimed at conserving migratory shorebirds in East Asian–Australasian Flyway for 6 sea-level rise (SLR) scenarios (50, 100, 150, 200, 250, 300 cm). The results shown here are at the 20% budget level. Investments in coastal sites are summarized regionally (black lines, regional boundaries; these are different from the nodes of flyways and are for presentation purposes only). Graphs indicate regional investments (y-axis) at the different SLR scenarios (x-axis).
