Beyond Pairwise Interactions: Multispecies Character Displacement in Mexican Freshwater Fish Communities

Abstract

Competition has long been recognized as a central force in shaping evolution, particularly through character displacement. Yet research on character displacement is biased, as it has focused almost exclusively on pairs of interacting species while ignoring multispecies interactions. Communities are seldom so simple that only pairs of species interact, and it is not clear whether inferences from pairwise interactions are sufficient to explain patterns of phenotypes in nature. Here, we test for character displacement in a natural system of freshwater fishes in western Mexico that contains up to four congeneric species of the genus Poeciliopsis. We analyzed body shape differences between populations with different numbers of competitors while accounting for confounding environmental variables. Surprisingly, we found evidence for convergent character displacement in populations of P. prolifica, P. viriosa, and P. latidens. We also found that the convergence in body shape was not consistently in the same direction, meaning that when three or more competitors co-occurred, we did not find more extreme body shapes compared with when there were only two competitors. Instead, when three or more competitors co-occurred, body shape was intermediate between the shape found with a pair of species and the shape found with no competitor present. This intermediate shape suggests that evolution in multispecies communities likely occurs in response to several competitors rather than to simple pairwise interactions. Overall, our results suggest that competition among multiple species is more complex than simple pairwise competitive interactions.

Ontogenetic shape trajectory of Trichomycterus areolatus varies in response to water velocity environment

“…In addition, we used centroid size (a multivariate measure of size) derived from this analysis to represent the stage of ontogenetic development. We excluded relative warps that individually accounted for < 1% of shape variation to avoid inflating the real degrees of freedom associated with analysis of shape variation [ 17 , 74 ]. Consequently, we used the first 12 of 22 relative warps for the body (accounting for 96.15% of total shape variation) and the first 9 of 10 relative warps for the head (accounting for 99.91% of total shape variation).…”

“…To determine the effects of velocity environment and ontogeny on shape variation in T . areolatus , we used a multivariate linear mixed model [ 16 , 17 , 74 ]. We analyzed body and head shape separately, using relative warps as the response variable.…”

“…We included the interaction between velocity environment and centroid size (ontogeny) to test for different patterns of shape variation across ontogeny between velocity environments. The multivariate linear mixed model required that the matrix of shape variables (relative warps) be vectorized such that each individual specimen was represented by 12 rows (body) or 9 rows (head) of data, and each row corresponded to one relative warp [ 74 ]. Thus, the response variable is transposed from a row in a matrix to a vector column of responses.…”

“…This vectorization creates the need for an index variable that preserves the identity of specific relative warps. This index variable is used as a predictor variable in the model much like time is used as a predictor in a typical repeated measures design [ 15 , 74 – 76 ]. Relative warps are principal components, and as such they are orthogonal to each other, they have a mean of zero, and their ordination is arbitrary relative to each other.…”

What Drives Life-History Variation in the Livebearing Fish Poeciliopsis prolifica? An Assessment of Multiple Putative Selective Agents

“…Life-history traits can be highly adaptive (Roff, 2002;Chapuis et al, 2017), and can evolve in response to a variety of selective pressures, both biotic and abiotic (Johnson and Bagley, 2011). Some demonstrated selective agents known to affect the evolution of life histories are population density (Reznick et al, 2002(Reznick et al, , 2012, predation (Martin, 1995;Johnson and Belk, 2001;Reznick et al, 2001;Roff, 2002;Chapuis et al, 2017), resource availability (Reznick and Yang, 1993;Grether et al, 2001;Roff, 2002;Pérez-Mendoza et al, 2014;Zani and Stein, 2018), and other environmental effects, such as water flow, elevation, toxicity, etc. (Badyaev and Ghalambor, 2001;Ghalambor et al, 2004;Zúñiga-Vega et al, 2007;Riesch et al, 2010Riesch et al, , 2014Johnson and Bagley, 2011;Banet et al, 2016;Heins and Baker, 2017;Santi et al, 2019).…”