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Relationship: 2147


A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Increased, Male Biased Sex Ratio leads to Decrease, Population growth rate

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes.Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Aromatase inhibition leads to male-biased sex ratio via impacts on gonad differentiation adjacent Low Brendan Ferreri-Hanberry (send email) Under Development: Contributions and Comments Welcome WPHA/WNT Endorsed
Androgen receptor agonism leading to male-biased sex ratio adjacent Evgeniia Kazymova (send email) Open for citation & comment WPHA/WNT Endorsed

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.  More help
Term Scientific Term Evidence Link
zebrafish Danio rerio Low NCBI
Sphenodon punctatus Sphenodon punctatus High NCBI
Strigops habroptilus Strigops habroptilus High NCBI
Lacerta vivipara Zootoca vivipara Low NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Male High

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
Adults High

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

Long-term maintenance of viable populations is dependent on the nature of interactions between males and females. One commonly used metric for capturing these interactions is evaluation of deviations from normal of the relative number of males versus females in a population. The ratio of males versus females needed for successful sexual reproduction varies by taxa, with some species requiring a one-to-one relationship, while in other species far fewer males than females may suffice in terms of producing an adequate number of fertile embryos to maintain a population. However, even in species potentially requiring fewer males than females to maintain a viable population, at some point a male-biased population could become problematic in terms of having an adequate number of males to fertilize eggs produced by females or, in the longer term, ensure a robust level of genetic diversity in a population. Further, in situations where a population is male-biased relative to conditions considered normal for a given species, overall productivity may be negatively impacted due to fewer females being available to produce eggs.

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings.  Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

As described below there are both empirical data and population modeling/simulation approaches that provide evidence for this KER.

Biological Plausibility
Addresses the biological rationale for a connection between KEupstream and KEdownstream.  This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured.   More help

The plausibility that a male-biased sex ratio would affect population status of different species is strong. For any given population, a male-biased sex ratio suggests that the number of available breeding females is reduced. If the male-biased sex ratio persists and/or increases over time, the offspring production will decrease and population size would be reduced. Additionally, for certain species, an increasing number of males could cause negative behavioral responses, for example, a higher competition for mating leading to more aggressive behaviors that can result in reduced adult survival rates for both male and females.  A reduced effective population also affects genetic diversity, which can further reduce population viability. 

Uncertainties and Inconsistencies
Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

Studies at the population level can be quite challenging in terms of required resources and, given the number of variables that might simultaneously influence a population, interpretation of results. Consequently, evaluation of population status in the context of adverse outcome pathways often relies upon model predictions that almost always are applicable only to a limited number of--sometimes one--species because of requirements associated with model parameterization. Given this, although it is entirely reasonable from an evolutionary perspective that male-biased sex ratios will negatively impact populations of a given species, it can be difficult to fully assess what this impact may be.  

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references.  More help

Population status can be impacted by a multitude of interacting biotic and abiotic variables, some of which could entirely supersede the effects of a male-biased sex ratio. For example, under conditions of severe food limitations or a regime of extreme temperature there may be no production of young irrespective of male:female sex ratios.

Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help

Brown et al. (2015) and Miller et al. (2022) provide examples for zebrafish and fathead minnows, respectively, of approaches used to establish quantitative response-response relationships between male-biased sex ratios and population size/trends. In general, however, population models almost always rely on female productivity rather than male contributions to forecast population status.

Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help

The time-scale for this KER is entirely dependent on the life-cyle of the organism of interest. Small, short-lived animal species could experience population-level alterations due to biased sex ratios in days to weeks, while impacts on larger, long-lived species may take years to decades. 

Known Feedforward/Feedback loops influencing this KER
Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

It is difficult to define what form a feedforward/feedback loop might take for this KER. This would likely largely be a function of the stressor causing a male-biased population. If the stressor was short-term (e.g., affecting one age cohort) the situation might be self-correcting, as opposed to a longer-term stressor that continually causes a male-biased sex ratio, which theoretically should usually result in population extirpation. 

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

Any sexually-reproducing species theoretically could experience male-biased sex ratios and consequent population-level effects.


List of the literature that was cited for this KER description. More help

Brown, A. R., Owen, S. F., Peters, J., Zhang, Y., Soffker, M., Paull, G. C., Hosken, D. J., Wahab, M. A., & Tyler, C. R. (2015). Climate change and pollution speed declines in zebrafish populations. Proceedings of the National Academy of Sciences of the United States of America112(11), E1237–E1246.

Clout, M. & Elliott, G. & Robertson, B. (2002). Effects of supplementary feeding on the offspring sex ratio of Kakapo: a dilemma for the conservation of a polygynous parrot. Biological Conservation. 107. 13-18. 10.1016/S0006-3207(01)00267-1. 

Grayson, K. L., Mitchell, N. J., Monks, J. M., Keall, S. N., Wilson, J. N., & Nelson, N. J. (2014). Sex ratio bias and extinction risk in an isolated population of Tuatara (Sphenodon punctatus). PloS one9(4), e94214. 

Le Galliard, J. F., Fitze, P. S., Ferrière, R., & Clobert, J. (2005). Sex ratio bias, male aggression, and population collapse in lizards. Proceedings of the National Academy of Sciences of the United States of America, 102(50), 18231–18236. 

Miller, D.H., D.L. Villeneuve, K.J. Santana-Rodriguez and G.T. Ankley. 2022. A multi-dimensional matrix model for predicting the effects of male-biased sex ratios on fish populations. Environmental Toxicology and Chemistry. 41, 1066-1077

Robertson, B. C., Elliott, G. P., Eason, D. K., Clout, M. N., & Gemmell, N. J. (2006). Sex allocation theory aids species conservation. Biology letters, 2(2), 229–231.