📝 SummarXiv

Abstract

In fisheries ecology, species abundance data are often collected by multiple surveys, each with unique characteristics. This article focuses on Atlantic sea scallop abundance data along the northeast coast of the United States, collected from two bottom trawl surveys which cover a larger spatial domain but have low catch efficiency, and a dredge survey which is more efficient but limited to domains where the species are believed to be present. To model such data, integrated species distribution models (ISDMs) have been proposed to incorporate information from multiple surveys, by including common environmental effects along with correlated survey-specific spatial fields. However, while flexible, these ISDMs can be susceptible to overfitting, which can complicate interpretability of the shared environmental effects and potentially lead to poor predictive performance. To overcome these drawbacks, we introduce a novel single index ISDM, built from a single index (with spatial random effects) that represents a latent measure of the true species distribution, and survey-specific catch efficiency functions which map the single index to the survey-specific expected catch. Our results show that the single index ISDM offers more meaningful interpretations of the environmental effects and survey catch efficiency differences, while potentially achieving better predictive performance than existing ISDMs.