Contributed Paper Quantifying Eradication Success: the Removal of Feral Pigs from Santa Cruz Island, California DAVID S. L. RAMSEY, ∗ § JOHN PARKES,† AND SCOTT A. MORRISON‡ ∗ Landcare Research, Private Bag 11052, Palmerston North, New Zealand †Landcare Research, P.O. Box 40, Lincoln 7640, New Zealand ‡The Nature Conservancy, 201 Mission Street, 4th Floor, San Francisco, CA 94105, U.S.A. Abstract: A major challenge facing pest-eradication efforts is determining when eradication has been achieved. When the pest can no longer be detected, managers have to decide whether the pest has actu- ally been eliminated and hence to decide when to terminate the eradication program. For most eradication programs, this decision entails considerable risk and is the largest single issue facing managers of such pro- grams. We addressed this issue for an eradication program of feral pigs (Sus scrofa) from Santa Cruz Island, California. Using a Bayesian approach, we estimated the degree of confidence in the success of the eradication program at the point when monitoring failed to detect any more pigs. Catch-effort modeling of the hunting ef- fort required to dispatch pigs during the eradication program was used to determine the relationship between detection probability and searching effort for different hunting methods. We then used these relationships to estimate the amount of monitoring effort required to declare eradication successful with criteria that either set a threshold for the probability that pigs remained undetected (type I error) or minimized the net expected costs of the eradication program (cost of type I and II errors). For aerial and ground-based monitoring techniques, the amount of search effort required to declare eradication successful on the basis of either criterion was highly dependent on the prior belief in the success of the program unless monitoring intensities exceeded 30 km of searching effort per square kilometer of search area for aerial monitoring and, equivalently, 38 km for ground monitoring. Calculation of these criteria to gauge the success of eradication should form an essential component of any eradication program as it allows for a transparent assessment of the risks inherent in the decision to terminate the program. Keywords: Bayesian statistics, catch-effort models, detection probability, pest eradication, risk management, Sus scrofa Cuantificaci´ on del ´ Exito de Erradicaci´ on: La Remoci´ on de Cerdos Cimarrones de la Isla Santa Cruz, California Resumen: Un reto mayor de los esfuerzos de erradicaci´ on de plagas es la determinaci´ on de cuando se ha alcanzado la erradicaci´ on. Cuando una plaga ya no es detectada los manejadores tienen que decidir s´ ı la plaga ha sido eliminada realmente y, por lo tanto, decidir cu´ ando terminar un programa de erradicaci´ on. Para la mayor´ ıa de los programas, esta decisi´ on representa riesgo considerable y es el principal tema que enfrentan los manejadores de tales programas. Atendimos este tema para un programa de erradicaci´ on de cerdos (Sus scrofa) cimarrones de la Isla Santa Cruz, California. Utilizando un enfoque Bayesiano, estimamos el nivel de confianza del ´ exito del programa de erradicaci´ on en el punto cuando el monitoreo no detect´ o m´ as cerdos. Utilizamos modelos del esfuerzo-captura del esfuerzo de cacer´ ıa requerido para sacrificar cerdos durante el programa de erradicaci´ on para determinar la relaci´ on entre la probabilidad de detecci´ on y el esfuerzo de b´ usqueda para diferentes m´ etodos de caza. Posteriormente utilizamos estas relaciones para estimar el esfuerzo de monitoreo requerido para declarar el´exito de la erradicaci´ on con criterios que definen un umbral para la probabilidad de que cerdos permanezcan sin detecci´ on (error tipo I) o minimizan los costos §Current address: Arthur Rylah Institute for Environmental Research, P.O. Box 137, Heidelberg 3084, Victoria, Australia, email david.ramsey@ dse.vic.gov.au Paper submitted March 24, 2008; revised manuscript accepted August 6, 2008. 449 Conservation Biology, Volume 23, No. 2, 449–459 C 2008 Society for Conservation Biology DOI: 10.1111/j.1523-1739.2008.01119.x