With these points in mind it is immediately obvious that Southeast Alaska (Table 4), which has only 9 high-score birds, offers far less potential for bird problems than does the Aleutian area (Table 5), which has 24 high-score species. The planning agency could make some immediate decisions on site priorities and research funding based on such information.

Discussion

We are convinced that the OVI principle expressed here will become a useful management tool with all sorts of possible applications. We recognize some difficulties with the present version, but believe it is timely to present the system so that a broader range of thought, improvements, and application can be applied to it.

Of prime importance is the system's simplicity. The use of four levels of value for each factor, instead of five or more, is an attempt to simplify. Ian McHarg (1969) has shown that extremely complex land-use values can be graphically compared and displayed by using three levels in a way that is useful to decision makers. The difficulty of using more levels of value was indicated by Sparrowe and Wight (1975) who used up to 10 levels, enormously complicating the problem of dealing with low-quality information, which is often all that is available. The use of scores of 0, 1, 3, 5 instead of 0, 1, 2, 3 for 20 factors enabled us to use the convenient 100 points instead of 60 points as the maximum potential total score for any species.

The 20 factors that were evaluated are admittedly arbitrary; with refinement and more detailed data they could be adjusted to show better separation between affected species. The decision to use 20 factors instead of more or less again relates to simplicity. This appears to be the minimum number that will assure species separation and that can be neatly displayed.

Table 3. Oil Vulnerability Index (OVI) for families of birds of the Northeast Pacific marine habitats, excluding rare and endangered species in the scoring.
FamilyNumber of speciesTotal OVIOVI per species
AverageRange
Loons—Gaviidae42195547-65
Grebes—Podicipedidae31484944-56
Albatrosses—Diomedeidae21025150-52
Shearwaters—Procellaridae42085247-57
Storm-petrels—Hydrobatidae21306563-67
Cormorants—Phalacrocoracid42355952-63
Herons—Ardeidae1292929
Waterfowl—Anatidae331,7655332-78
Eagles and Hawks—Accipitridae2773919-58
Ospreys—Pandionidae1373737
Falcons—Falconidae1414141
Cranes—Gruidae1242424
Rails and Coots—Rallidae1333333
Oystercatchers—Haematopodidae1656565
Plovers—Charadriidae72874126-57
Sandpipers—Scolopacidae228573924-59
Phalaropes—Phalaropodidae21206058-62
Jaegers and Skuas—Stercorariidae31234139-43
Gulls and Terns—Laridae167304632-66
Auks—Alcidae151,1647870-88
Kingfishers—Alcedinidae1282828
Crows—Corvidae2683421-47
Total and Mean1286,4905119-88

The system will be much more useful when it is expanded to the subspecific level. Many Holarctic species are represented in the Northeast Pacific by a single race that would have a much higher OVI than the species as a whole. For example, the OVI for the Peale's peregrine falcon (Falco peregrinus pealei) confined to marine habitats within the Pacific region would be high; and the endangered Aleutian Canada goose (Branta canadensis leucopareia) would score 100 points instead of the 34 we show for Canada geese (B. c.). If Tables 4 and 5 showed subspecies, the differences in value would be more marked.

Tables 4 and 5 are for broad geographical areas. A comparison between smaller areas would probably show more dramatic differences.

Because the dearth of easily available, applicable information poses a problem in evaluating the various factors, our scoring was conservative. Experts on the various avian families can doubtless refine the scoring. If this system proves useful, investigators will begin to acquire the information needed for more precise evaluations. Ultimate perfection may never be achieved; however, as with the field guides, the fact of minor professional disagreement should not destroy the system's utility.