Long-term monitoring of marine ecosystems is critical to assessing how global processes such as natural environmental variation and climate change affect marine populations. Ichthyoplankton surveys provide one approach to such monitoring. We conducted weekly fish egg collections off the Scripps Institution of Oceanography Pier (La Jolla, CA, USA) for three years (2014-2017) and added a second sampling site near the La Jolla kelp forest for one year (2017). Fish eggs were identified using DNA barcoding and data were compared to previous work from Pier surveys from 2012-2014. We documented large interannual variability in fish egg abundance associated with climatic fluctuations, including an El Niño event captured during our sampling years. Overall egg abundance was reduced by > 50% during periods of anomalously warm water in 2014-2016. Fish egg abundance rebounded in 2017 and was accompanied by a phenological shift of peak spawning activity. We found interannual fish egg abundance may be linked with upwelling regimes and winter temperatures. Across the period of joint sampling, we found no distinct differences in community composition between the Pier (soft bottom) and kelp forest habitat we sampled (2 km distant). Long-term monitoring of fish spawning can contribute to our understanding of how natural environmental variation such as El Niño events affect fish reproductive activity. This understanding may extend to trends in marine resource availability associated with climate and aid in evaluating the efficacy of existing management efforts.

There is urgent need for effective and efficient monitoring of marine fish populations. Monitoring eggs and larval fish may be more informative than that traditional fish surveys since ichthyoplankton surveys reveal the reproductive activities of fish populations, which directly impact their population trajectories. Ichthyoplankton surveys have turned to molecular methods (DNA barcoding & metabarcoding) for identification of eggs and larval fish due to challenges of morphological identification. In this study, we examine the effectiveness of using metabarcoding methods on mock communities of known fish egg DNA. We constructed six mock communities with known ratios of species. In addition, we analyzed two samples from a large field collection of fish eggs and compared metabarcoding results with traditional DNA barcoding results. We examine the ability of our metabarcoding methods to detect species and relative proportion of species identified in each mock community. We found that our metabarcoding methods were able to detect species at very low input proportions; however, levels of successful detection depended on the markers used in amplification, suggesting that the use of multiple markers is desirable. Variability in our quantitative results may result from amplification bias as well as interspecific variation in mitochondrial DNA copy number. Our results demonstrate that there remain significant challenges to using metabarcoding for estimating proportional species composition; however, the results provide important insights into understanding how to interpret metabarcoding data. This study will aid in the continuing development of efficient molecular methods of biological monitoring for fisheries management.