Estimating Endangered Species Interaction Risk With the Kalman Filter

Abstract

AbstractTo address the tradeoff between biodiversity conservation in marine ecosystems and fishing opportunity, it is important to quantify the risk of endangered species interactions in commercial fisheries. We propose a Kalman filter suitable for rare events to estimate the endangered leatherback turtle take risk in the California drift gillnet fishery in the years 1990–2010, conditional on spatiotemporal factors that affect take rates. Results suggest interaction risk has remained stable, but with substantial variation over the spatiotemporal distribution of effort. Our methods might also apply to recreation demand analysis with rare event risk, or to applications involving irregularly spaced observations, like trade‐level stock market data.