Leptospirosis, the disease caused by pathogenic bacteria of the genus Leptospira, is a major health burden for humans and animals worldwide and a recognized risk for military personnel. Leptospira has circulated for decades in California sea lions (CSL) (Zalophus californianus), and an outbreak of a near-identical strain was recently discovered in endangered island foxes (Urocyon littoralis) on Santa Rosa Island (SRI), California. This raised concerns about risks to island fox subspecies on three nearby Department of Defense islands.
This project studied the ecology of Leptospira in these two species of concern, and built models to analyze how non-stationary conditions affect disease incidence and impacts. The objectives were: (1) to identify the source of the current Leptospira outbreak on SRI, (2) to understand the drivers of Leptospira dynamics in CSL and build a model to make short- and long-term predictions, and (3) to study the ecology of Leptospira in island foxes and build a model to project its future impacts on SRI and assess management strategies under changing conditions.
With the project partners, the project team extended long-term studies of host demography and Leptospira spread in both CSL and island foxes. They conducted laboratory analyses on newly collected and archived samples to detect current infections and prior exposure to Leptospira. They conducted whole genome sequencing of Leptospira isolates from marine and terrestrial hosts and analyzed the sequences to understand transmission routes in the coastal ecosystem. They developed mechanistic and statistical models to reveal underlying processes, project trends under changing conditions, and assess management strategies.
The source of the outbreak in reintroduced SRI foxes was spillover from another terrestrial host species on the island, almost certainly island spotted skunks. After an initial epidemic wave in 2006-2007, Leptospira has now established endemic circulation in SRI foxes. The data-driven transmission model projects pathogen persistence under all foreseeable scenarios. Fortunately, the demographic impacts of the disease are moderate, and the fox population has continued to grow. The models also indicate that island fox populations on other islands are vulnerable to invasion by Leptospira, and predict similar impacts. In the CSL system, the project team analyzed 30 years of annual leptospirosis outbreaks to show that outbreak intensity is driven by the combined effects of susceptible supply and fluctuations in oceanographic conditions. A model capturing these effects could explain 50% of interannual variability and could make real- time predictions of upcoming outbreak intensity. The model also projected that stronger environmental fluctuations under climate change would cause more extreme peaks and troughs in Leptospira activity. This prediction was borne out by the spontaneous fadeout of Leptospira from 2013-2017 during a marine heatwave, followed by the largest outbreak on record in 2018.
This project generated new knowledge and tools to support management of two wildlife species of concern in the California coastal ecosystem. By extending long-term field studies and analyzing the data with mathematical and statistical models to reveal underlying processes, the project team generated evidence-based guidance for managers and set priorities for future research. Data-driven modeling tools for both systems can be adapted to address future needs of species managers. New insights into Leptospira ecology will advance conservation and public health goals, and long-term time series data are priceless assets to study on-going global change.