Identifying Anomalous Reports of Putatively Extinct Species and Why It Matters

Abstract:  As species become very rare and approach extinction, purported sightings can stir controversy, especially when scarce management resources are at stake. We used quantitative methods to identify reports that do not fit prior sighting patterns. We also examined the effects of including records that meet different evidentiary standards on quantitative extinction assessments for four charismatic bird species that might be extinct: Eskimo Curlew ( Numenius borealis ), Ivory-billed Woodpecker ( Campephilus principalis ), Nukupu`u ( Hemignathus lucidus ), and O`ahu `Alauahio ( Paroreomyza maculata ). For all four species the probability of there being a valid sighting today, given the past pattern of verified sightings, was estimated to be very low. The estimates of extinction dates and the chance of new sightings, however, differed considerably depending on the criteria used for data inclusion. When a historical sighting record lacked long periods without sightings, the likelihood of new sightings declined quickly with time since the last confirmed sighting. For species with this type of historical record, therefore, new reports should meet an especially high burden of proof to be acceptable. Such quantitative models could be incorporated into the International Union for Conservation of Nature's Red List criteria to set evidentiary standards required for unconfirmed sightings of "possibly extinct" species and to standardize extinction assessments across species.     

A Quantitative Method for Estimating Probable Public Costs of Hurricanes

/ A method is presented for estimating probable public costs resulting from damage caused by hurricanes, measured as local government expenditures approved for reimbursement under the Stafford Act Section 406 Public Assistance Program. The method employs a multivariate model developed through multiple regression analysis of an array of independent variables that measure meteorological, socioeconomic, and physical conditions related to the landfall of hurricanes within a local government jurisdiction. From the regression analysis we chose a log-log (base 10) model that explains 74% of the variance in the expenditure data using population and wind speed as predictors. We illustrate application of the method for a local jurisdiction-Lee County, Florida, USA. The results show that potential public costs range from $4.7 million for a category 1 hurricane with winds of 137 kilometers per hour (85 miles per hour) to $130 million for a category 5 hurricane with winds of 265 kilometers per hour (165 miles per hour). Based on these figures, we estimate expected annual public costs of $2.3 million. These cost estimates: (1) provide useful guidance for anticipating the magnitude of the federal, state, and local expenditures that would be required for the array of possible hurricanes that could affect that jurisdiction; (2) allow policy makers to assess the implications of alternative federal and state policies for providing public assistance to jurisdictions that experience hurricane damage; and (3) provide information needed to develop a contingency fund or other financial mechanism for assuring that the community has sufficient funds available to meet its obligations. KEY WORDS: Hurricane; Public costs; Local government; Disaster recovery; Disaster response; Florida; Stafford Act