A process‐based model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages

Abstract

Habitat dynamics interacting with species dispersal abilities could generate gradients in species diversity and prevalence of species traits when the latter are associated with species dispersal potential. Using a process-based model of diversification constrained by a dispersal parameter, we simulated the interplay between reef habitat dynamics during the past 140 million years and dispersal, shaping lineage diversification history and assemblage composition globally. The emerging patterns from the simulations were compared to current prevalence of species traits related to dispersal for 6315 tropical reef fish species. We found a significant spatial congruence between the prevalence of simulated low dispersal values and areas with a large proportion of species characterized by small adult body size, narrow home range mobility behaviour, pelagic larval duration shorter than 21 days and diurnal activity. Species characterized by such traits were found predominantly in the Indo-Australian Archipelago and the Caribbean Sea. Furthermore, the frequency distribution of the dispersal parameter was found to match empirical distributions for body size, PLD and home range mobility behaviour. Also, the dispersal parameter in the simulations was associated to diversification rates and resulted in trait frequency matching empirical distributions. Overall, our findings suggest that past habitat dynamics, in conjunction with dispersal processes, influenced diversification in tropical reef fishes, which may explain the present-day geography of species traits.

Trophic innovations fuel reef fish diversification

“…Although recent studies have independently explored these potential ecological mechanisms or geographical factors underlying reef fish diversification patterns (e.g., refs. 16,25,[29][30][31][32] ), they are yet to be examined in a comparative analytical framework capable of quantifying relative support.…”

gen3sis: the general engine for eco-evolutionary simulations on the origins of biodiversity

“…below 1 Ma) and/or explored few mechanisms, i.e. simplified landscape or single acceptance criteria [24,41,42,110].…”

“…Further exploration possibilities may include: (iv) revealing the mechanisms behind agedependent speciation and extinction patterns [102,108,156]; (v) contrasts between terrestrial and aquatic ecosystems [16]; and (vi) calculations of uncertainty resulting from climatic and geological dynamics [e.g. 24,25,26,41,42]. Gen3sis can support these research frontiers as a general tool for formalizing and studying existing theories associated with the origin of biodiversity, testing new hypotheses against data, and making predictions about future biodiversity trajectories (Table 4).…”

“…Several case studies have illustrated the feasibility and usefulness of computer models in guiding intuition for the interpretation of empirical data [24,26,[38][39][40][41][42]. Moreover, models have reproduced realistic large-scale biodiversity patterns, such as along latitude [25,43,44], by considering climate and geological dynamics [24,26,42], and population isolation by considering dispersal ability and geographic distance [24][25][26][38][39][40][41][42]. For example, computer models were used to examine how oceans' paleogeography influenced biodiversity dynamics in marine ecosystems [24,[41][42][43].…”

“…Moreover, models have reproduced realistic large-scale biodiversity patterns, such as along latitude [25,43,44], by considering climate and geological dynamics [24,26,42], and population isolation by considering dispersal ability and geographic distance [24][25][26][38][39][40][41][42]. For example, computer models were used to examine how oceans' paleogeography influenced biodiversity dynamics in marine ecosystems [24,[41][42][43]. Nevertheless, the potential of computer models to enlighten the mechanisms underlying biodiversity patterns remains largely untapped.…”