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|Assessing the Reliability of Species Distribution Model Projections in the Face of Climate and Ecosystem Regime Shifts: Small Pelagic Fishes in the California Current Ecosystem
|Presenting Author Name
|Presenting Author Affiliation
|East Carolina University
|Presenting Author Email
|Marine fisheries, climate impacts, species distribution modeling
|Type of Presentation
Species distribution models (SDMs) are a common tool used to project changes in organismal occurrence, abundance, and phenology under climate change. An often untested assumption of SDMs is that relationships between organisms and the environment are stationary. To evaluate this, we examined whether habitat use by larvae of four small pelagic fishes in the California Current remained steady across three different types of climate and ecosystem regime shifts. Generalized additive models (GAMs) were constructed separately for each regime using temperature, salinity, dissolved oxygen, and mesozooplankton volume as predictors of fish occurrence. We assessed non-stationarity with six metrics: 1) variables included in SDMs; 2) linear vs. non-linear form; 3) rank order of deviance explained by variables; 4) response curve shape; 5) degree of responsiveness of fishes to a variable; 6) preferred range of environmental variables used by fishes. Across all species and time periods, non-stationarity was ubiquitous, affecting at least one of the six indicators. Non-stationarity was most common among periods defined by changes in zooplankton productivity. The relationship between fishes and temperature was more stable than relationships with other environmental variables. Respectively, sardine, chub mackerel, anchovy, and jack mackerel exhibited non-stationarity across 83%, 75%, 61%, and 58% of indicators. Relatively small present-day differences among GAMs in habitat suitability became amplified by the end of the 21st century under two climate change scenarios. This suggests that the widespread non-stationarity in how fishes utilize their environment could hamper our ability to reliably project how species will respond to future changes.