A Multidimensional Matrix Model for Predicting the Effects of Male‐Biased Sex Ratios on Fish Populations

Abstract

Laboratory experiments have established that exposure to certain endocrine‐active substances prior to and/or during the period of sexual differentiation can lead to skewed sex ratios in fish. However, the potential long‐term population impact of biased sex ratio depends on multiple factors including the life history of the species and whether the ratio is male or female‐biased. In the present study, we describe a novel multidimensional, density‐dependent matrix model that analyzes age class‐structure of both males and females over time, allowing for the quantitative evaluation of the effects of biased sex ratio on population status. This approach can be used in conjunction with field monitoring efforts and/or laboratory testing to link effects on sex ratio due to chemical and/or nonchemical stressors to adverse outcomes in whole organisms and populations. For demonstration purposes, we applied the model to evaluate population trajectories for fathead minnow (Pimephales promelas) exposed to prochloraz, an aromatase inhibitor, during sexual differentiation. The model also was used to explore the population impact in a more realistic exposure scenario in which both adult and early life stages of fish are exposed concurrently to prochloraz, which, in addition to altering sex ratio during development, can decrease vitellogenin and egg production in adult females. For each exposure scenario, the model was used to analyze total population size, numbers of females and of males, and sex specific recruitment of the F1 generation. The present study illustrates the utility of multidimensional matrix population models for ecological risk assessment in terms of integrating effects across a population of an organism even when chemical effects on individuals are manifested via different pathways depending on life stage. Environ Toxicol Chem 2022;41:1066–1077. Published 2022. This article is a U.S. Government work and is in the public domain in the USA.

Projection of Interspecific Competition (PIC) Matrices: A Conceptual Framework for Inclusion in Population Risk Assessments

“…For example, a qAOP has been developed and applied relating in vitro measures of a chemical's ability to inhibit sex steroid synthesis that would result in inhibition of reproduction in vivo and, ultimately, reduced population numbers in the fathead minnow (Cheng et al, 2016;Conolly et al, 2017;Villeneuve et al, 2021). Employing the AOP framework to access diverse sources/types of chemical effects data enables population-level inferences of possible impacts for a much larger universe of chemicals/chemical mixtures than would otherwise be possible (see Etterson & Ankley, 2021;Miller et al, 2007Miller et al, , 2013Miller et al, , 2015Miller et al, , 2022Moe et al, 2021;Murphy et al, 2018;Perkins et al, 2019).…”

“…Many ecological risk assessments culminate in the analysis of population-level impacts. Input needed to support modelbased predictions of population status has historically included measured effects of chemical and nonchemical stressors on survival, development, and reproduction in individual organisms under controlled conditions (Barnthouse et al, 2008;Caswell, 2001;Forbes et al, 2016;Grimm & Thorbek, 2014;Hanson & Stark, 2012;Miller & Ankley, 2004;Miller et al, 2013Miller et al, , 2015Miller et al, , 2020Miller et al, , 2022Raimondo et al, 2018;Spromberg & Meador, 2005). Recent improvements in the ability to rapidly measure stressor-induced biochemical and molecular alterations in biological systems, as well as developments in bioinformatics and pathway-based predictive approaches to understand the toxicological consequences of these perturbations, have provided additional types of data for population modeling (Ankley et al, 2010).…”

AOP Report: Adverse Outcome Pathways for Aromatase Inhibition or Androgen Receptor Agonism Leading to Male‐Biased Sex Ratio and Population Decline in Fish

“…Testes can be easily distinguished from ovaries visually in adult fathead minnows (KE 1790); however, it may be necessary to employ histological and magnification techniques for this assessment in juvenile fish (see Leino et al, 2005). Finally, translation of the consequences of male‐skewed populations (KE 1791) on fathead minnow population dynamics (KE 360) can be predicted using the modeling construct described by Miller et al (2022).…”

“…Because E2 is a major regulator of normal female gonad development (Guiguen et al, 2010), reductions in signaling required for ovarian differentiation are decreased, and the bipotential gonad will default to development of testes (Yin et al, 2017; Zhang et al, 2017), thus plausibly resulting in a male‐biased sex ratio in a population. A male‐biased sex ratio would logically lead to a reduction in the number of breeding females such that, over time, decreases in recruitment would result in population decline (Miller et al, 2022). While molecular processes linking AR activation (AOP 376) to increased testis differentiation in fish are less well understood than for CYP19 inhibition (AOP 346), there also is a substantial amount of empirical evidence showing that this is a biologically plausible pathway.…”

“…To address the lack of AOPs relevant to HPG effects in early-life stage fish, the goal of the effort summarized in the present study was to develop two AOPs linking early developmental perturbations to masculinization in later life stages. Development of the AOPs described in our study is complemented by a parallel effort to advance a modeling construct to predict impacts of male-skewed cohorts on fish populations (Miller et al, 2022).…”