The degree of spatial overlap between size groups within a population (hereafter, spatial overlap) influences key biological processes, such as connectivity and competition within a population. However, how changes in spatial overlap with abundance vary across populations, particularly in relation to life history traits, is largely unknown. In this study, we analyzed spatial time series data from 1982 to 2019 to investigate how spatial overlap responded to changing abundance in 56 marine fish populations across four regions. Our results show that 33 populations exhibited positive relationships between spatial overlap and abundance in over 50% of size group pairs. In the North Sea and on the Scottish West Coast, certain size group pairs showed a stronger spatial overlap-abundance relationship in populations characterized by slower growth (higher growth coefficient, longer lifespan, later maturity) and larger body sizes (greater maximum and asymptotic size), compared to populations with faster growth and smaller body sizes. This suggests that size groups within slower-growing and larger-bodied populations tend to spatially segregate more rapidly when abundance declines, making them vulnerable to local disturbances such as in hotspots of fishing pressure and habitat destruction. Our analytical approach suggests that the spatial overlap-abundance relationship could serve as a useful vulnerability index for conservation and management efforts.

Ample evidence has indicated shifts in distribution of fish populations in response to environmental stress. However, most studies focused at the whole population scale. This neglects the spatial dynamics between groups of different body size (body size groups), that fundamentally shapes the spatial structure of a population. Here, we explored the mechanisms that modulate spatial dynamics of body size groups, and applied our analyses to three North Sea fish populations which experienced severe declines in biomass from 1977 to 2019: Atlantic cod (Gadus morhua), haddock (Melanogrammus aeglefinus), and whiting (Merlangius merlangius). All three populations exhibited strong declines in the overlapped area between body size groups in winter over 43 years, yet their mechanisms differed. These declines were either due to (1) different magnitudes of contraction of the distribution area of body size groups; and/or (2) different speeds and directions of spatial shift among various body size groups, both increasing spatial segregation within populations. These patterns were either associated with ocean warming, and/or declining population biomass, and such associations often varied according to distinct body size groups. Our analytical approach provides a powerful tool for identifying vulnerable populations under environmental stress and can be generalized to study a variety of size/age structured populations at various ecosystem types.

Studying complex metazoan communities requires taxonomic expertise and laborious work if done using the traditional morphological approach. Nowadays, the popular use of molecular-based methods accompanied by massively parallel sequencing (MPS) provides rapid and higher resolution diversity analyses. However, diversity estimates derived from the molecular-based approach can be biased by the co-detection of environmental DNA (eDNA), pseudogene contamination, and PCR amplification biases. Here, we constructed microcrustacean zooplankton mock communities to compare species diversity and composition estimates from PCR-based methods using genomic (gDNA) and complementary DNA (cDNA), metatranscriptomic transcripts, and morphology data. Mock community analyses show that gDNA mitochondrial cytochrome c oxidase I (mtCOI) amplicons inflate species richness due to environmental and nontarget species sequence contamination. Significantly higher amplicon sequence variant (ASV) and nucleotide diversity in gDNA amplicons than cDNA indicated the presence of putative pseudogenes. Last, PCR-based methods failed to detect the most abundant species in mock communities due to priming site mismatch. Overall, metatranscriptomic transcripts provided estimates of species richness and composition that closely resembled morphological data. The use of metatranscriptomic transcripts was further tested in field samples. The results showed that it could provide consistent species diversity estimates among biological and technical replicates while allowing monitoring of the zooplankton temporal species composition changes using different mitochondrial markers. These findings show that community characterization based on metatranscriptomic transcripts reflects the actual community more than PCR-based approaches.

Predator and prey α-diversity are often positively associated; yet, underlying mechanisms remain unclear. We attempt to address this issue by deciphering how α-diversity of predator and prey influences each other’s community assembly processes and subsequently determines α-diversity. The occurrence of assembly processes were indicated by the mean pairwise taxonomic index within a community (αMPTI), assuming assembly processes left traceable imprints on species’ phylogeny. Specifically, αMPTI quantifies deviations of observed phylogenetic distances from that of random, thus indicating that non-random/deterministic assembly processes are in action. Less negative αMPTI, which hints at the occurrence of weaker homogeneous deterministic assembly processes, is expected to increase α-diversity of the community. We hypothesize that higher predator and prey α-diversity make each other’s αMPTI less negative, which then increases their α-diversity. To test the hypothesis, we calculated Shannon diversity and αMPTI for heterotrophic nanoflagellates (HNF; predator) and bacteria (prey) communities in the East China Sea. The HNF Shannon diversity was found to make the αMPTI of bacteria less negative, which then increased bacterial Shannon diversity. In contrast, bacterial Shannon diversity did not affect HNF’s αMPTI. We provide evidence that top-down control underpins the positive α-diversity association among trophic levels in microbes of the East China Sea.