Adaptive and unequal probability survey designs for environmental management

Abstract

Designing an efficient large-area survey is a challenge, especially in environmental science when many populations are rare and clustered. Adaptive and unequal probability sampling designs are appealing when populations are rare and clustered because survey effort can be targeted to subareas of high interest. For example, higher density subareas are usually of more interest than lower density areas. Adaptive and unequal probability sampling offer flexibility for designing a long term survey because they can accommodate changes in survey objectives, changes in underlying environmental habitat, and changes in species-habitat models.