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Relationship: 2938

Title

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

Decreased, Viable Offspring leads to Decrease, Population growth rate

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Decreased, Viable Offspring

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Decrease, Population growth rate

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
PPARalpha Agonism Leading to Decreased Viable Offspring via Decreased 11-Ketotestosterone	adjacent	Moderate	Low	Arthur Author (send email)	Open for citation & comment

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
teleost fish	teleost fish		NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help

Sex	Evidence
Unspecific

Life Stage Applicability

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

Term	Evidence
All life stages

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

Population growth rate which measures the per capita rate of population increase over a time interval is proportional to the instantaneous birth rate (number of births per individual per unit of time and the instantaneous death rate (number of deaths per individual per unit of time) (Caswell 2001, Miller and Ankley 2004, Gotelli 2008, Vandermeer and Goldberg 2013, Murray and Sandercock 2020). Decreases in viable offspring could therefore lead to decreased population growth rate, recognizing that other factors (e.g., immigration/emigration, intraspecific and interspecific competition, predation, disease) influence population growth. Population models could be employed to aide in understanding how changes to population growth rate result from various levels of decline in recruitment of young of year fish.

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

There is no empirical data suitable for evaluating the dose-response, temporal, or incidence concordance between a reduction in the number of viable offspring and decrease in population growth rate. However, population modeling/simulation approaches could be applied in investigating 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

A decrease in population growth rate whereby the per capita rate of population change is negative over time can result from either a decline in the instantaneous birth rate and/or an increasein the instantaneous death rate (Caswell 2001, Miller and Ankley 2004, Gotelli 2008, Vandermeer and Goldberg 2013, Murray and Sandercock 2020). While the number of eggs produced by female fish would not be directly impacted, impaired spermatogenesis in male fish that results in decreased oocyte fertilization and/or a reduction in viable offspring would reduce the population growth rate over time as fewer eggs on average would survive to become young of year fish. Thus, the reproductive potential of female fish adjusted for the inability of fertilized eggs to progress and hatch into viable offspring would be expected to result in a decline in recruitment and contribution of offspring to the next generation (a decline in net reproductive rate) (Caswell 2001, Gotelli 2008, Vandermeer and Goldberg 2013).

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

There is very limited empirical data for this KER; thus, evidence is based on biological plausibility and population models.

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

There is limited empirical data for this KER. Population models are often parameterized based on information from a single species. Studies at the population level rely upon observation and estimation of a number of species-specific variables that influence population growth rate (e.g. age or stage specific estimates of survival and fecundity), each of which has an associated uncertainty. There are also uncertainties in extending the population model (extrapolation of model predictions) to be applicable to other species.

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

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

Response-response Relationship

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

Decreased oocyte fertilization and/or a reduction in viable offspring would result in reduced survival of eggs to become young of year fish. This in turn would result in a lower population growth rate over time.

Time-scale

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 at which decrease in viable offspring would impact population levels is dependent on a species life cycle, with the potential for impacts in the short term (i.e. days or weeks) for short-lived species and much longer (years) for long-lived species.

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

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

References

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

Caswell H. 2001. Matrix Population Models. Sinauer Associates, Inc., Sunderland, MA, USA.

Galic N, Hommen U, Baveco JM, van den Brink PJ (2010) Potential application of population models in the European ecological risk assessment of chemicals. II. Review of models and their potential to address environmental protection aims. Integr Environ Assess Manag 6:338–360.

Gotelli NJ. 2008. A Primer of Ecology. Sinauer Associates, Inc., Sunderland, MA, USA.

Miller DH, Ankley GT. 2004. Modeling impacts on populations: Fathead minnow (Pimephales promelas) exposure to the endocrine disruptor 17b-trenbolone as a case study. Ecotox Environ Saf 59:1–9.

Mittelbach GG, McGill BJ (2019) Community ecology. Oxford University Press, Oxford.

Murray DL, Sandercock BK. 2020. Population ecology in practice. Wiley-Blackwell, Oxford UK, 448 pp.

Vandermeer JH, Goldberg DE. 2013. Population ecology: first principles. Princeton University Press, Princeton, NJ USA.