Population ecology and decision analysis to inform seabird conservation

Abstract

Seabirds are among the most threatened vertebrate groups globally, facing a range of anthropogenic threats from invasive species and fisheries bycatch to increasingly pervasive climate-driven changes in ocean ecosystems. Despite the availability of proven conservation strategies, effective management of seabird populations is often constrained by ecological complexity, logistical challenges, and uncertainty in species-specific responses. Seabirds’ long lifespans, low fecundity, and use of vast marine habitats create additional challenges for monitoring and decision-making. At the same time, these species play critical ecological roles as nutrient vectors and ecosystem indicators. As climate change alters the structure and productivity of marine environments, there is an urgent need to better understand how seabird populations respond to environmental variability—and how that understanding can inform conservation decisions. The research I present here explores the use of population ecology and decision analysis to evaluate seabird demography and improve conservation outcomes using case studies from the California Channel Islands, USA. First, I developed a novel daily nest survival model to assess how spatial and temporal variation in oceanographic conditions affect reproductive success for the Cassin’s Auklet (Ptychoramphus aleuticus), a sentinel species of marine climate change (Chapter 2). I then extend this work by building an integrated population model to quantify how environmental drivers influence demographic rates, abundance, and population growth across two colonies and to determine the role of demographic buffering in population stability (Chapter 3). In a separate case study, I model marine and terrestrial drivers of nest survival for a rare seabird with a restricted breeding range, the Scripps’s Murrelet (Synthliboramphus scrippsi), to support targeted management and conservation efforts (Chapter 4). Finally, I apply structured decision-making tools to evaluate uncertainty in seabird management and conservation, using constructed value of information to prioritize research and monitoring priorities across six species (Chapter 5). Together, this research shows how linking ecological modeling with decision analysis can improve seabird conservation under dynamic and uncertain conditions.