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Relationship: 2013

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

Increased Mortality 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
Acetylcholinesterase Inhibition leading to Acute Mortality via Impaired Coordination & Movement​ adjacent Kristie Sullivan (send email) Under development: Not open for comment. Do not cite
Acetylcholinesterase inhibition leading to acute mortality adjacent Moderate Moderate Dan Villeneuve (send email) Under Development: Contributions and Comments Welcome Under Development
Deiodinase 2 inhibition leading to increased mortality via reduced posterior swim bladder inflation adjacent Moderate Moderate Dries Knapen (send email) Under Development: Contributions and Comments Welcome EAGMST Approved
Deiodinase 2 inhibition leading to increased mortality via reduced anterior swim bladder inflation adjacent Moderate Moderate Dries Knapen (send email) Under Development: Contributions and Comments Welcome EAGMST Approved
Deiodinase 1 inhibition leading to increased mortality via reduced posterior swim bladder inflation adjacent Moderate Moderate Dries Knapen (send email) Under Development: Contributions and Comments Welcome EAGMST Approved
Deiodinase 1 inhibition leading to increased mortality via reduced anterior swim bladder inflation adjacent Moderate Moderate Dries Knapen (send email) Under Development: Contributions and Comments Welcome EAGMST Approved
Thyroperoxidase inhibition leading to increased mortality via reduced anterior swim bladder inflation adjacent Moderate Moderate Dries Knapen (send email) Under Development: Contributions and Comments Welcome EAGMST Approved
Thyroperoxidase inhibition leading to altered visual function via altered retinal layer structure adjacent Moderate Moderate Lucia Vergauwen (send email) Open for citation & comment EAGMST Under Review
Thyroperoxidase inhibition leading to altered visual function via decreased eye size adjacent Lucia Vergauwen (send email) Under development: Not open for comment. Do not cite Under Development
Thyroperoxidase inhibition leading to altered visual function via altered photoreceptor patterning adjacent Lucia Vergauwen (send email) Under development: Not open for comment. Do not cite Under Development
Inhibition of Fyna leading to increased mortality via decreased eye size (Microphthalmos) adjacent High High Vid Modic (send email) Open for citation & comment
GSK3beta inactivation leading to increased mortality via defects in developing inner ear adjacent High High Vid Modic (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
zebrafish Danio rerio High NCBI
fathead minnow Pimephales promelas High NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Unspecific Moderate

Life Stage Applicability

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

Increased mortality in the reproductive population may lead to a declining population. This depends on the excess mortality due to the applied stressor and the environmental parameters such as food availability and predation rate. Most fish species are r-strategist, meaning they produce a lot of offspring instead of investing in parental care. This results in natural high larval mortality causing only a small percentage of the larvae to survive to maturity. If the excess larval mortality due to a stressor is small, the population dynamics might result in constant population size. Should the larval excess be more significant, or last on the long-term, this will affect the population. To calculate the long-term persistence of the population, population dynamic models should be used.

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

Survival rate is an obvious determinant of population size and is therefore included in population modeling (e.g., Miller et al., 2020).

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
  • Survival to reproductive maturity is a parameter of demographic significance. Assuming resource availability (i.e., food, habitat, etc.) is not limiting to the extant population, sufficient mortality in the reproductive population may ultimately lead to declining population trajectories.
  • Under some conditions, reduced larval survival may be compensated by reduced predation and increased food availability, and therefore not result in population decline (Stige et al., 2019).
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
  • The extent to which larval mortality affects population size could depend on the fraction of surplus mortality compared to a natural situation.
  • There are scenarios in which individual mortality may not lead to declining population size. These include instances where populations are limited by the availability of habitat and food resources, which can be replenished through immigration. Effects of mortality in the larvae can be compensated by reduced competition for resources (Stige et al., 2019).
  • The direct impact of pesticides on migration behavior can be difficult to track in the field, and documentation of mortality during migration is likely underestimated (Eng 2017).

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

Taxonomic: All organisms must survive to reproductive age in order to reproduce and sustain populations. The additional considerations related to survival made above are applicable to other fish species in addition to zebrafish and fathead minnows with the same reproductive strategy (r-strategist as described in the theory of MaxArthur and Wilson (1967). The impact of reduced survival on population size is even greater for k-strategists that invest more energy in a lower number of offspring.

Life stage: Density dependent effects start to play a role in the larval stage of fish when free-feeding starts (Hazlerigg et al., 2014).

Sex: This linkage is independent of sex.

References

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

Alekseeva SM, Rudenko AI. 2018. Modeling of optimum fishing population. Marine Intellectual Technologies. 3(4):142-146.

Beaudouin, R., Goussen, B., Piccini, B., Augustine, S., Devillers, J., Brion, F., Pery, A.R., 2015. An individual-based model of zebrafish population dynamics accounting for energy dynamics. PloS one 10, e0125841.

Boreman J. 1997. Methods for comparing the impacts of pollution and fishing on fish populations. Transactions of the American Fisheries Society. 126(3):506-513.

Caswell, H., 2000. Matrix population models. Sinauer Sunderland, MA, USA.

Eng, M.L., Stutchbury, B.J.M. & Morrissey, C.A. Imidacloprid and chlorpyrifos insecticides impair migratory ability in a seed-eating songbird. Sci Rep 7, 15176 (2017)

Hazlerigg, C.R., Lorenzen, K., Thorbek, P., Wheeler, J.R., Tyler, C.R., 2012. Density-dependent processes in the life history of fishes: evidence from laboratory populations of zebrafish Danio rerio. PLoS One 7, e37550.

Jacobsen NS, Essington TE. 2018. Natural mortality augments population fluctuations of forage fish. Fish and Fisheries. 19(5):791-797.

MacArthur, R., Wilson, E., 1967. The Theory of Island Biogeography. Princeton: Princeton Univ. Press. 203 p.

Miller, D.H., Ankley, G.T., 2004. Modeling impacts on populations: fathead minnow (Pimephales promelas) exposure to the endocrine disruptor 17β-trenbolone as a case study. Ecotoxicology and Environmental Safety 59, 1-9.

Miller, D.H., Clark, B.W., Nacci, D.E. 2020. A multidimensional density dependent matrix population model for assessing risk of stressors to fish populations. Ecotoxicology and environmental safety 201, 110786

Pinceel, T., Vanschoenwinkel, B., Brendonck, L., Buschke, F., 2016. Modelling the sensitivity of life history traits to climate change in a temporary pool crustacean. Scientific reports 6, 29451.

Rearick, D.C., Ward, J., Venturelli, P., Schoenfuss, H., 2018. Environmental oestrogens cause predation-induced population decline in a freshwater fish. Royal Society open science 5, 181065.

Schäfers, C., Oertel, D., Nagel, R., 1993. Effects of 3, 4-dichloroaniline on fish populations with differing strategies of reproduction. In: Braunbeck, T. , Hanke, W and Segner, H. (eds) Ecotoxicology and Ecophysiology, VCH, Weinheim, 133-146.

Stige, L.C., Rogers, L.A., Neuheimer, A.B., Hunsicker, M.E., Yaragina, N.A., Ottersen, G., Ciannelli, L., Langangen, Ø., Durant, J.M., 2019. Density‐and size‐dependent mortality in fish early life stages. Fish and Fisheries 20, 962-976.Hazlerigg, C.R.E., Tyler, C.R., Lorenzen, K., Wheeler, J.R., Thorbek, P., 2014. Population relevance of toxicant mediated changes in sex ratio in fish: An assessment using an individual-based zebrafish (Danio rerio) model. Ecological Modelling 280, 76-88.

Stige, L.C., Rogers, L.A., Neuheimer, A.B., Hunsicker, M.E., Yaragina, N.A., Ottersen, G., Ciannelli, L., Langangen, O., Durant, J.M., 2019. Density- and size-dependent mortality in fish early life stages. Fish and Fisheries 20, 962-976.