Patrick N. Halpin

A population of humpback whales (Megaptera novaeangliae) spends the austral summer feeding on Antarctic krill (Euphausia superba) along the Western Antarctic Peninsula (WAP). These whales acquire their annual energetic needs during an episodic feeding season in high latitude waters that must sustain long-distance migration and fasting on low-latitude breeding grounds. Antarctic krill are broadly distributed along the continental shelf and nearshore waters during the spring and early summer, and move closer to land during late summer and fall, where they overwinter under the protective and nutritional cover of sea ice. We apply a novel space-time utilization distribution method to test the hypothesis that humpback whale distribution reflects that of krill: spread broadly during summer with increasing proximity to shore and associated embayments during fall. Humpback whales instrumented with satellite-linked positional telemetry tags (n = 5), show decreased home range size, amount of ...

... on Everglades Tree Islands Kirsten Hofmockel, Curtis J. Richardson, and Patrick N. Halpin 8.1 Introduction ... More recent studies of the origin, classification, and ecology of tree islands were presented in an excellent volume by Sklar and van der Valk (2002). ...

The ocean is a dynamic environment with ocean currents and winds moving surface waters across large distances. Many animals that live in the ocean, particularly in offshore regions, are mobile in space and in time, as are most human users. Spatial management responses have typically partitioned the ocean into different regions with fixed management boundaries; in some regions a particular activity may be forbidden; in another it may be permitted but regulated; and in others it may be allowed without any regulation. In contrast, dynamic ocean management (DOM) changes in space and time in response to the shifting nature of the ocean and its users. DOM techniques have been applied in a limited number of situations around the world, notably for fisheries, to regulate or restrict the capture of a particular marine species. DOM requires scientific, technological, management, legal, and policy capacity across a range of elements. The article outlines seven of these elements and describes r...

SummaryThe vulnerability of coastal landscapes to sea level rise is compounded by the existence of extensive artificial drainage networks initially built to lower water tables for agriculture, forestry, and human settlements. These drainage networks are found in landscapes with little topographic relief where channel flow is characterized by bi-directional movement across multiple time-scales and related to precipitation, wind, and tidal patterns. The current configuration of many artificial drainage networks exacerbates impacts associated with sea level rise such as salt-intrusion and increased flooding. This suggests that in the short-term, drainage networks might be managed to mitigate sea level rise related impacts. The challenge, however, is that hydrologic processes in regions where channel flow direction is weakly related to slope and topography require extensive parameterization for numerical models which is limited where network size is on the order of a hundred or more kilometers in total length. Here we present an application of graph theoretic algorithms to efficiently investigate network properties relevant to the management of a large artificial drainage system in coastal North Carolina, USA. We created a digital network model representing the observation network topology and four types of drainage features (canal, collector and field ditches, and streams). We applied betweenness-centrality concepts (using Dijkstra's shortest path algorithm) to determine major hydrologic flowpaths based off of hydraulic resistance. Following this, we identified sub-networks that could be managed independently using a community structure and modularity approach. Lastly, a betweenness-centrality algorithm was applied to identify major shoreline entry points to the network that disproportionately control water movement in and out of the network. We demonstrate that graph theory can be applied to solving management and monitoring problems associated with sea level rise for poorly understood drainage networks in advance of numerical methods.