<td>Under development: Not open for comment. Do not cite</td>
<td>Under Development: Contributions and Comments Welcome</td>
<td></td>
<td>1.29</td>
<td>Under Development</td>
</tr>
</tbody>
</table>
</div>
</div>
<!-- Abstract Section, text as generated by author -->
<div id="abstract">
<h2>Abstract</h2>
<p>This AOP describes the linkages between agonism of the estrogen receptor (ER) and population relevant impacts on reproductive function in a range of oviparous vertebrates including amphibia, birds and fish. The information in this AOP for ER agonism does not apply to mammalian species and also not to invertebrates.</p>
<p> </p>
<p><br />
Amphibians are sensitive to ER agonists during the transformation from larval tadpole to juvenile frog as these include critical periods of metamorphic development and sex differentiation that may be particularly sensitive to endocrine disruption. Larvae exposed to ER agonists during mid-metamorphosis show developmental effects, a subsequent strong female-biased sex ratio which suggests that transient early life-stage exposure to ER agonists can produce effects on the reproductive organs that persist into the beginning of adult life-stages. Birds are also known to be vulnerable to ER agonists causing disruption of estrogen-regulated functions such as sexual differentiation and sexual behaviour. Model species such as the Japanese quail have been widely used as a model for studying various long-term effects after embryonic exposure to ER agonists. In terms of teleost fish, exposure to ER agonists leads to a suite of adverse outcomes depending upon whether exposures occur during or beyond the larval, juvenile and adult life-stages. For example, aquatic exposure to potent ER agonists during the larval and juvenile life-stages may leads to gonadal and renal pathology and skewed-sex ratios in adult fish (potentially 100% females). Larval, juvenile and adult male fish exposed to the same ER agonists display abnormal plasma or whole body levels of vitellogenin (VTG). Cumulative fecundity in adult populations is also adversely affected by ER agonists and this is an important endpoint in the OECD Test Guideline 229 Fish Short Term Reproduction Assay. In summary, this AOP has utility in supporting the application of test methods for detecting ER agonists, or in silico predictions of the ability of chemicals to act as ER agonists and cause impaired sexual development and reproductive dysfunction.</p>
<h2>Abstract</h2>
<hr>
<p>This AOP describes the linkages between agonism of the estrogen receptor (ER) and population relevant impacts on reproductive function in a range of oviparous vertebrates including amphibia, birds and fish. The information in this AOP for ER agonism does not apply to mammalian species and also not to invertebrates.
</p><p><br />
</p><p><br />
Amphibians are sensitive to ER agonists during the transformation from larval tadpole to juvenile frog as these include critical periods of metamorphic development and sex differentiation that may be particularly sensitive to endocrine disruption. Larvae exposed to ER agonists during mid-metamorphosis show developmental effects, a subsequent strong female-biased sex ratio which suggests that transient early life-stage exposure to ER agonists can produce effects on the reproductive organs that persist into the beginning of adult life-stages. Birds are also known to be vulnerable to ER agonists causing disruption of estrogen-regulated functions such as sexual differentiation and sexual behaviour. Model species such as the Japanese quail have been widely used as a model for studying various long-term effects after embryonic exposure to ER agonists. In terms of teleost fish, exposure to ER agonists leads to a suite of adverse outcomes depending upon whether exposures occur during or beyond the larval, juvenile and adult life-stages. For example, aquatic exposure to potent ER agonists during the larval and juvenile life-stages may leads to gonadal and renal pathology and skewed-sex ratios in adult fish (potentially 100% females). Larval, juvenile and adult male fish exposed to the same ER agonists display abnormal plasma or whole body levels of vitellogenin (VTG). Cumulative fecundity in adult populations is also adversely affected by ER agonists and this is an important endpoint in the OECD Test Guideline 229 Fish Short Term Reproduction Assay. In summary, this AOP has utility in supporting the application of test methods for detecting ER agonists, or in silico predictions of the ability of chemicals to act as ER agonists and cause impaired sexual development and reproductive dysfunction.
</p>
<br>
</div>
<!-- Background Section, text as generated by author -->
<div id="background">
<br>
</div>
<!-- AOP summary, includes summary of each of the events associated with this aop -->
<!-- Overall assessment section, *** what is included here? *** -->
<div id="overall_assessment">
<h2>Overall Assessment of the AOP</h2>
<p>In terms of the criteria associated with Key Events in this AOP, the following observations have been made as shown in parentheses []:
</p><p>1. concordance of dose-response relationships?; [There is strong dose-response relationship concordance over a wide range of experimental studies using ER agonists in well-defined animals models, including amphibians, birds and fish];
</p><p>2. temporal concordance among the key events and adverse effect?; [There is strong temporal concordance from partial and full life-cycle studies using ER agonists in well-defined animals models];
</p><p>3. strength, consistency, and specificity of association of adverse effect and initiating event?; [In fish, there is a strong and consistent association between ER agonist exposure, disruption of sexual development and reproductive dysfunction. The same is true for amphibians and birds although the published studies are less numerous.];
</p><p>4. biological plausibility, coherence, and consistency of the experimental evidence?; [For the oviparous species frequently studied to date, there is a high level of biological plausibility, coherence, and consistency across the published experimental evidence];
</p><p>5. alternative mechanisms that logically present themselves and the extent to which they may distract from the postulated AOP?; [Other mechanisms of relevance to estrogen-mediated sexual development include the disruption of the steroidogenic pathways (eg see the AOP for aromatase inhibition in fish) and this alterative AOP should be considered alongside ER agonism in the context of elevated plasma VTG levels, disrupted sexual development of reproductive dysfunction. The possibility of other AOPs arisign should be kept in mind through critical analysis of the updated pree-reviewed literature];
</p><p>6. uncertainties, inconsistencies and data gaps?; [An important aspect of uncertainty is quantifying the degree to which disrupted sexual development leads to a population-relevant impact via reproductive dysfunction. Experimental and validated population modelling is a key need to address this data gap and uncertainty. In the author's view, there are no major scientific inconsistencies with regard to the ER agonism AOP and associated Key Events].
<p>In terms of the criteria associated with Key Events in this AOP, the following observations have been made as shown in parentheses []:</p>
<p>1. concordance of dose-response relationships?; [There is strong dose-response relationship concordance over a wide range of experimental studies using ER agonists in well-defined animals models, including amphibians, birds and fish];</p>
<p>2. temporal concordance among the key events and adverse effect?; [There is strong temporal concordance from partial and full life-cycle studies using ER agonists in well-defined animals models];</p>
<p>3. strength, consistency, and specificity of association of adverse effect and initiating event?; [In fish, there is a strong and consistent association between ER agonist exposure, disruption of sexual development and reproductive dysfunction. The same is true for amphibians and birds although the published studies are less numerous.];</p>
<p>4. biological plausibility, coherence, and consistency of the experimental evidence?; [For the oviparous species frequently studied to date, there is a high level of biological plausibility, coherence, and consistency across the published experimental evidence];</p>
<p>5. alternative mechanisms that logically present themselves and the extent to which they may distract from the postulated AOP?; [Other mechanisms of relevance to estrogen-mediated sexual development include the disruption of the steroidogenic pathways (eg see the AOP for aromatase inhibition in fish) and this alterative AOP should be considered alongside ER agonism in the context of elevated plasma VTG levels, disrupted sexual development of reproductive dysfunction. The possibility of other AOPs arisign should be kept in mind through critical analysis of the updated pree-reviewed literature];</p>
<p>6. uncertainties, inconsistencies and data gaps?; [An important aspect of uncertainty is quantifying the degree to which disrupted sexual development leads to a population-relevant impact via reproductive dysfunction. Experimental and validated population modelling is a key need to address this data gap and uncertainty. In the author's view, there are no major scientific inconsistencies with regard to the ER agonism AOP and associated Key Events].</p>
<a href="#Sex_Applicability"> Sex Applicability</a><br />
In terms of the taxonomic domains of applicability, exposure to ER agonists is capable of disrupting sexual development and causing reproductive dysfunction in oviparous species suchas amphibians, birds and fish (see examples of peer-revised literature cited below).
In terms of the taxonomic domains of applicability, exposure to ER agonists is capable of disrupting sexual development and causing reproductive dysfunction in oviparous species suchas amphibians, birds and fish (see examples of peer-revised literature cited below).</p>
</div>
<!-- potential consierations, text as entered by author -->
<!-- reference section, text as of right now but should be changed to be handled as table -->
<div id="references">
<h2>References</h2>
<hr>
<p><br />
Dang, Z., Traas, T., Vermeire, T. (2011) Evaluation of the fish short term reproduction assay for detecting endocrine disrupters. Chemosphere 85: 1592-1603
</p><p>Halldin, K., Axelsson, J., Brunström, B., (2005) Effects of endocrine modulators on sexual differentiation and reproductive function in male Japanese quail. Brain Research Bulletin 65: 211-218
</p><p>Hogan, N.S., Duarte, P., Wade, M.G., Lean, D.R.S., Trudeau, V.L. (2008) Estrogenic exposure affects metamorphosis and alters sex ratios in the northern leopard frog (Rana pipiens): Identifying critically vulnerable periods of development. General and Comparative Endocrinology 156: 515-523
</p><p>Hutchinson T.H. (2002) Impacts of endocrine disrupters on fish development: opportunities for adapting OECD Test Guideline 210. Environmental Sciences 9: 439-450
</p><p>Länge R., Hutchinson T.H., Croudace C.P., Siegmund F., Schweinfurth H., Hampe P., Panter G.H., Sumpter J.P. (2001) Effects of the synthetic oestrogen 17-ethinylestradiol over the life-cycle of the fathead minnow. Environmental Toxicology and Chemistry 20: 1216–1227
</p><p>Leino, R.L., Jensen,K.M., Ankley, G.T. (2005) Gonadal histology and characteristic histopathology associated with endocrine disruption in the adult fathead minnow (Pimephales promelas). Environmental Toxicology and Pharmacology 19: 85-98
</p><p>Ottinger, M.N., Carro, T., Bohannon, M., Baltos,L., Marcell, A.M., McKernan, M., Dean, K.M., Lavoie, E., Abdelnabi, M. (2013) Assessing effects of environmental chemicals on neuroendocrine systems: Potential mechanisms and functional outcomes. General and Comparative Endocrinology 190: 194-202
</p>
<br>
<p><br />
Dang, Z., Traas, T., Vermeire, T. (2011) Evaluation of the fish short term reproduction assay for detecting endocrine disrupters. Chemosphere 85: 1592-1603</p>
<p>Halldin, K., Axelsson, J., Brunström, B., (2005) Effects of endocrine modulators on sexual differentiation and reproductive function in male Japanese quail. Brain Research Bulletin 65: 211-218</p>
<p>Hogan, N.S., Duarte, P., Wade, M.G., Lean, D.R.S., Trudeau, V.L. (2008) Estrogenic exposure affects metamorphosis and alters sex ratios in the northern leopard frog (Rana pipiens): Identifying critically vulnerable periods of development. General and Comparative Endocrinology 156: 515-523</p>
<p>Hutchinson T.H. (2002) Impacts of endocrine disrupters on fish development: opportunities for adapting OECD Test Guideline 210. Environmental Sciences 9: 439-450</p>
<p>Länge R., Hutchinson T.H., Croudace C.P., Siegmund F., Schweinfurth H., Hampe P., Panter G.H., Sumpter J.P. (2001) Effects of the synthetic oestrogen 17-ethinylestradiol over the life-cycle of the fathead minnow. Environmental Toxicology and Chemistry 20: 1216–1227</p>
<p>Leino, R.L., Jensen,K.M., Ankley, G.T. (2005) Gonadal histology and characteristic histopathology associated with endocrine disruption in the adult fathead minnow (Pimephales promelas). Environmental Toxicology and Pharmacology 19: 85-98</p>
<p>Ottinger, M.N., Carro, T., Bohannon, M., Baltos,L., Marcell, A.M., McKernan, M., Dean, K.M., Lavoie, E., Abdelnabi, M. (2013) Assessing effects of environmental chemicals on neuroendocrine systems: Potential mechanisms and functional outcomes. General and Comparative Endocrinology 190: 194-202</p>
<p><p>Reduction of cumulative fecundity and spawning following exposure to low levels of TDCIPP (15, 46 and 90 nM) has been reported in 3 different zebrafish studies (Liu et al., 2013; Wang et al., 2015a; Zhu et al., 2015).</p>
</p>
<br>
<!-- end Evidence for Perturbation of This Event by Stressors -->
<h4>Domain of Applicability</h4>
<br>
<!-- loop to find taxonomic applicability under event -->
<p>Cumulative fecundity and spawning can, in theory, be evaluated for any egg laying animal.</p>
<br>
</div>
<!-- event text -->
<h4>Key Event Description</h4>
<p>Spawning refers to the release of eggs. Cumulative fecundity refers to the total number of eggs deposited by a female, or group of females over a specified period of time.</p>
<p>Cumulative fecundity and spawning can, in theory, be evaluated for any egg laying animal.</p>
<br>
<h4>Key Event Description</h4>
<p>Spawning refers to the release of eggs. Cumulative fecundity refers to the total number of eggs deposited by a female, or group of females over a specified period of time.</p>
<h4>How it is Measured or Detected</h4>
<p>In laboratory-based reproduction assays (e.g., OECD Test No. 229; OECD Test No. 240), spawning and cumulative fecundity can be directly measured through daily observation of egg deposition and egg counts.</p>
<h4>How it is Measured or Detected</h4>
<p>In laboratory-based reproduction assays (e.g., OECD Test No. 229; OECD Test No. 240), spawning and cumulative fecundity can be directly measured through daily observation of egg deposition and egg counts.</p>
<p>In some cases, fecundity may be estimated based on gonado-somatic index (<a href="http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=env/jm/mono(2008)22&doclanguage=en">OECD 2008</a>).</p>
<br>
<h4>Regulatory Significance of the AO</h4>
<p>Cumulative fecundity is the most apical endpoint considered in the OECD 229 Fish Short Term Reproduction Assay. The OECD 229 assay serves as screening assay for endocrine disruption and associated reproductive impairment (<a href="http://www.oecd-ilibrary.org/environment/test-no-229-fish-short-term-reproduction-assay_9789264185265-en">OECD 2012</a>). Fecundity is also an important apical endpoint in the Medaka Extended One Generation Reproduction Test (MEOGRT; <a href="http://www.oecd-ilibrary.org/environment/test-no-240-medaka-extended-one-generation-reproduction-test-meogrt_9789264242258-en">OECD Test Guideline 240</a>; OECD 2015).</p>
<h4>Regulatory Significance of the AO</h4>
<p>Cumulative fecundity is the most apical endpoint considered in the OECD 229 Fish Short Term Reproduction Assay. The OECD 229 assay serves as screening assay for endocrine disruption and associated reproductive impairment (<a href="http://www.oecd-ilibrary.org/environment/test-no-229-fish-short-term-reproduction-assay_9789264185265-en">OECD 2012</a>). Fecundity is also an important apical endpoint in the Medaka Extended One Generation Reproduction Test (MEOGRT; <a href="http://www.oecd-ilibrary.org/environment/test-no-240-medaka-extended-one-generation-reproduction-test-meogrt_9789264242258-en">OECD Test Guideline 240</a>; OECD 2015).</p>
<p>A variety of fish life cycle tests also include cumulative fecundity as an endpoint (<a href="http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=env/jm/mono(2008)22&doclanguage=en">OECD 2008</a>).</p>
<p> </p>
<br>
<h4>References</h4>
<ul>
<h4>References</h4>
<ul>
<li>OECD 2008. Series on testing and assessment, Number 95. Detailed Review Paper on Fish Life-cycle Tests. OECD Publishing, Paris. ENV/JM/MONO(2008)22.</li>
<li>OECD (2015), <em>Test No. 240: Medaka Extended One Generation Reproduction Test (MEOGRT)</em>, OECD Publishing, Paris.<br />
<td><a href="/aops/23">Aop:23 - Androgen receptor agonism leading to reproductive dysfunction (in repeat-spawning fish)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/25">Aop:25 - Aromatase inhibition leading to reproductive dysfunction</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/29">Aop:29 - Estrogen receptor agonism leading to reproductive dysfunction</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/30">Aop:30 - Estrogen receptor antagonism leading to reproductive dysfunction</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/100">Aop:100 - Cyclooxygenase inhibition leading to reproductive dysfunction via inhibition of female spawning behavior</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/122">Aop:122 - Prolyl hydroxylase inhibition leading to reproductive dysfunction via increased HIF1 heterodimer formation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/123">Aop:123 - Unknown MIE leading to reproductive dysfunction via increased HIF-1alpha transcription</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/155">Aop:155 - Deiodinase 2 inhibition leading to reduced young of year survival via posterior swim bladder inflation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/156">Aop:156 - Deiodinase 2 inhibition leading to reduced young of year survival via anterior swim bladder inflation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/157">Aop:157 - Deiodinase 1 inhibition leading to reduced young of year survival via posterior swim bladder inflation </a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/158">Aop:158 - Deiodinase 1 inhibition leading to reduced young of year survival via anterior swim bladder inflation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/159">Aop:159 - Thyroperoxidase inhibition leading to reduced young of year survival via anterior swim bladder inflation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/101">Aop:101 - Cyclooxygenase inhibition leading to reproductive dysfunction via inhibition of pheromone release</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/102">Aop:102 - Cyclooxygenase inhibition leading to reproductive dysfunction via interference with meiotic prophase I /metaphase I transition</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/63">Aop:63 - Cyclooxygenase inhibition leading to reproductive dysfunction</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/103">Aop:103 - Cyclooxygenase inhibition leading to reproductive dysfunction via interference with spindle assembly checkpoint</a></td>
<td><a href="/aops/23">Aop:23 - Androgen receptor agonism leading to reproductive dysfunction (in repeat-spawning fish)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/25">Aop:25 - Aromatase inhibition leading to reproductive dysfunction</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/29">Aop:29 - Estrogen receptor agonism leading to reproductive dysfunction</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/30">Aop:30 - Estrogen receptor antagonism leading to reproductive dysfunction</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/100">Aop:100 - Cyclooxygenase inhibition leading to reproductive dysfunction via inhibition of female spawning behavior</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/122">Aop:122 - Prolyl hydroxylase inhibition leading to reproductive dysfunction via increased HIF1 heterodimer formation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/123">Aop:123 - Unknown MIE leading to reproductive dysfunction via increased HIF-1alpha transcription</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/155">Aop:155 - Deiodinase 2 inhibition leading to increased mortality via reduced posterior swim bladder inflation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/156">Aop:156 - Deiodinase 2 inhibition leading to increased mortality via reduced anterior swim bladder inflation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/157">Aop:157 - Deiodinase 1 inhibition leading to increased mortality via reduced posterior swim bladder inflation </a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/158">Aop:158 - Deiodinase 1 inhibition leading to increased mortality via reduced anterior swim bladder inflation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/159">Aop:159 - Thyroperoxidase inhibition leading to increased mortality via reduced anterior swim bladder inflation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/101">Aop:101 - Cyclooxygenase inhibition leading to reproductive dysfunction via inhibition of pheromone release</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/102">Aop:102 - Cyclooxygenase inhibition leading to reproductive dysfunction via interference with meiotic prophase I /metaphase I transition</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/63">Aop:63 - Cyclooxygenase inhibition leading to reproductive dysfunction</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/103">Aop:103 - Cyclooxygenase inhibition leading to reproductive dysfunction via interference with spindle assembly checkpoint</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/292">Aop:292 - Inhibition of tyrosinase leads to decreased population in fish</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/310">Aop:310 - Embryonic Activation of the AHR leading to Reproductive failure, via epigenetic down-regulation of GnRHR</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/16">Aop:16 - Acetylcholinesterase inhibition leading to acute mortality</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/312">Aop:312 - Acetylcholinesterase Inhibition leading to Acute Mortality via Impaired Coordination & Movement</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/334">Aop:334 - Glucocorticoid Receptor Agonism Leading to Impaired Fin Regeneration</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/336">Aop:336 - DNA methyltransferase inhibition leading to population decline (1)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/337">Aop:337 - DNA methyltransferase inhibition leading to population decline (2)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/338">Aop:338 - DNA methyltransferase inhibition leading to population decline (3)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/339">Aop:339 - DNA methyltransferase inhibition leading to population decline (4)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/340">Aop:340 - DNA methyltransferase inhibition leading to transgenerational effects (1)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/341">Aop:341 - DNA methyltransferase inhibition leading to transgenerational effects (2)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/289">Aop:289 - Inhibition of 5α-reductase leading to impaired fecundity in female fish</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/297">Aop:297 - Inhibition of retinaldehyde dehydrogenase leads to population decline</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/346">Aop:346 - Aromatase inhibition leads to male-biased sex ratio via impacts on gonad differentiation</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/326">Aop:326 - Thermal stress leading to population decline (3)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/325">Aop:325 - Thermal stress leading to population decline (2)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/324">Aop:324 - Thermal stress leading to population decline (1)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/363">Aop:363 - Thyroperoxidase inhibition leading to altered visual function via altered retinal layer structure</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/349">Aop:349 - Inhibition of 11β-hydroxylase leading to decresed population trajectory </a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/348">Aop:348 - Inhibition of 11β-Hydroxysteroid Dehydrogenase leading to decreased population trajectory </a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/376">Aop:376 - Androgen receptor agonism leading to male-biased sex ratio</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/386">Aop:386 - Deposition of ionizing energy leading to population decline via inhibition of photosynthesis</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/387">Aop:387 - Deposition of ionising energy leading to population decline via mitochondrial dysfunction</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/388">Aop:388 - Deposition of ionising energy leading to population decline via programmed cell death</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/389">Aop:389 - Oxygen-evolving complex damage leading to population decline via inhibition of photosynthesis</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/364">Aop:364 - Thyroperoxidase inhibition leading to altered visual function via decreased eye size</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/365">Aop:365 - Thyroperoxidase inhibition leading to altered visual function via altered photoreceptor patterning</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/399">Aop:399 - Inhibition of Fyna leading to increased mortality via decreased eye size (Microphthalmos)</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/410">Aop:410 - GSK3beta inactivation leading to increased mortality via defects in developing inner ear</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/216">Aop:216 - Deposition of energy leading to population decline via DNA strand breaks and follicular atresia</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/238">Aop:238 - Deposition of energy leading to population decline via DNA strand breaks and oocyte apoptosis</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/299">Aop:299 - Deposition of energy leading to population decline via DNA oxidation and follicular atresia</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/311">Aop:311 - Deposition of energy leading to population decline via DNA oxidation and oocyte apoptosis</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/444">Aop:444 - Ionizing radiation leads to reduced reproduction in Eisenia fetida via reduced spermatogenesis and cocoon hatchability</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/138">Aop:138 - Organic anion transporter (OAT1) inhibition leading to renal failure and mortality</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/177">Aop:177 - Cyclooxygenase 1 (COX1) inhibition leading to renal failure and mortality</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/97">Aop:97 - 5-hydroxytryptamine transporter (5-HTT; SERT) inhibition leading to population decline</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/203">Aop:203 - 5-hydroxytryptamine transporter inhibition leading to decreased reproductive success and population decline</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/218">Aop:218 - Inhibition of CYP7B activity leads to decreased reproductive success via decreased locomotor activity</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/219">Aop:219 - Inhibition of CYP7B activity leads to decreased reproductive success via decreased sexual behavior</a></td>
<td>AdverseOutcome</td>
</tr>
<tr>
<td><a href="/aops/323">Aop:323 - PPARalpha Agonism Leading to Decreased Viable Offspring via Decreased 11-Ketotestosterone</a></td>
<p>Consideration of population size and changes in population size over time is potentially relevant to all living organisms.</p>
<br>
</div>
<p>Consideration of population size and changes in population size over time is potentially relevant to all living organisms.</p>
<h4>Key Event Description</h4>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">A population can be defined as a group of interbreeding organisms, all of the same species, occupying a specific space during a specific time (Vandermeer and Goldberg 2003, Gotelli 2008). As the population is the biological level of organization that is often the focus of ecological risk</span> <span style="color:black">assessments, population growth rate (and hence population size over time) is important to consider within the context of applied conservation practices.</span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">If N is the size of the population and t is time, then the population growth rate (dN/dt) is proportional to the instantaneous rate of increase, r, which measures the per capita rate of population increase over a short time interval. Therefore, r, is a difference between the instantaneous birth rate (number of births per individual per unit of time; b) and the instantaneous death rate (number of deaths per individual per unit of time; d) [Equation 1]. Because r is an instantaneous rate, its units can be changed via division. For example, as there are 24 hours in a day, an r of 24 individuals/(individual x day) is equal to an r of 1 individual/(individual/hour) (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020). </span></span></span></span></p>
<p style="margin-left:144px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Equation 1: r = b - d</span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">This key event refers to scenarios where r < 0 (instantaneous death rate exceeds instantaneous birth rate).</span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Examining r in the context of population growth rate:</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A population will decrease to extinction when the instantaneous death rate exceeds the instantaneous birth rate (r < 0). </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black"> ● The smaller the value of r below 1, the faster the population will decrease to zero. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A population will increase when resources are available and the instantaneous birth rate exceeds the instantaneous death rate (r > 0)</span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black"> ● The larger the value that r exceeds 1, the faster the population can increase over time </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A population will neither increase or decrease when the population growth rate equals 0 (either due to N = 0, or if the per capita birth and death rates are exactly balanced). For example, the per capita birth and death rates could become exactly balanced due to density dependence and/or to the effect of a stressor that reduces survival and/or reproduction (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020). </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Effects incurred on a population from a chemical or non-chemical stressor could have an impact directly upon birth rate (reproduction) and/or death rate (survival), thereby causing a decline in population growth rate. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● Example of direct effect on r: Exposure to 17b-trenbolone reduced reproduction (i.e., reduced b) in the fathead minnow over 21 days at water concentrations ranging from 0.0015 to about 41 mg/L (Ankley et al. 2001; Miller and Ankley 2004). </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Alternatively, a stressor could indirectly impact survival and/or reproduction. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● Example of indirect effect on r: Exposure of non-sexually differentiated early life stage fathead minnow to the fungicide prochloraz has been shown to produce male-biased sex ratios based on gonad differentiation, and resulted in projected change in population growth rate (decrease in reproduction due to a decrease in females and thus recruitment) using a population model. (Holbech et al., 2012; Miller et al. 2022)</span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Density dependence can be an important consideration:</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● The effect of density dependence depends upon the quantity of resources present within a landscape. A change in available resources could increase or decrease the effect of density dependence and therefore cause a change in population growth rate via indirectly impacting survival and/or reproduction. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● This concept could be thought of in terms of community level interactions whereby one species is not impacted but a competitor species is impacted by a chemical stressor resulting in a greater availability of resources for the unimpacted species. In this scenario, the impacted species would experience a decline in population growth rate. The unimpacted species would experience an increase in population growth rate (due to a smaller density dependent effect upon population growth rate for that species). </span> </span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Closed versus open systems:</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● The above discussion relates to closed systems (there is no movement of individuals between population sites) and thus a declining population growth rate cannot be augmented by immigration. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● When individuals depart (emigrate out of a population) the loss will diminish population growth rate. </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Population growth rate applies to all organisms, both sexes, and all life stages.</span></span></span></span></p>
<p> </p>
<!-- event text -->
<h4>Key Event Description</h4>
<p>Maintenance of sustainable fish and wildlife populations (i.e., adequate to ensure long-term delivery of valued ecosystem services) is an accepted regulatory goal upon which risk assessments and risk management decisions are based.</p>
<br>
<h4>How it is Measured or Detected</h4>
<p>Population trajectories, either hypothetical or site specific, can be estimated via population modeling based on measurements of vital rates or reasonable surrogates measured in laboratory studies. As an example, Miller and Ankley 2004 used measures of cumulative fecundity from laboratory studies with repeat spawning fish species to predict population-level consequences of continuous exposure.</p>
<br>
<h4>Regulatory Significance of the AO</h4>
<p>Maintenance of sustainable fish and wildlife populations (i.e., adequate to ensure long-term delivery of valued ecosystem services) is a widely accepted regulatory goal upon which risk assessments and risk management decisions are based.</p>
<h4>How it is Measured or Detected</h4>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Population growth rate (instantaneous growth rate) can be measured by sampling a population over an interval of time (i.e. from time t = 0 to time t = 1). The interval of time should be selected to correspond to the life history of the species of interest (i.e. will be different for rapidly growing versus slow growing populations). The population growth rate, r, can be determined by taking the difference (subtracting) between the initial population size, N</span><sub><span style="font-size:9pt"><span style="color:black">t=0 </span></span></sub><span style="color:black">(population size at time t=0), and the population size at the end of the interval, N</span><sub><span style="font-size:9pt"><span style="color:black">t=1 </span></span></sub><span style="color:black">(population size at time t = 1), and then subsequently dividing by the initial population size. </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">The diversity of forms, sizes, and life histories among species has led to the development of a vast number of field techniques for estimation of population size and thus population growth over time (Bookhout 1994, McComb et al. 2021). </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● For stationary species an observational strategy may involve dividing a habitat into units. After setting up the units, samples are performed throughout the habitat at a select number of units (determined using a statistical sampling design) over a time interval (at time t = 0 and again at time t = 1), and the total number of organisms within each unit are counted. The numbers recorded are assumed to be representative for the habitat overall, and can be used to estimate the population growth rate within the entire habitat over the time interval. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● For species that are mobile throughout a large range, a strategy such as using a mark-recapture method may be employed (i.e. tags, bands, transmitters) to determine a count over a time interval (at time = 0 and again at time =1). </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Population growth rate can also be estimated using mathematical model constructs (for example, ranging from simple differential equations to complex age or stage structured matrix projection models and individual based modeling approaches), and may assume a linear or nonlinear population increase over time (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020). The AOP framework can be used to support the translation of pathway-specific mechanistic data into responses relevant to population models and output from the population models, such as changing (declining) population growth rate, can be used to assess and manage risks of chemicals (Kramer et al. 2011). As such, this translational capability can increase the capacity and efficiency of safety assessments both for single chemicals and chemical mixtures (Kramer et al. 2011). </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Some examples of modeling constructs used to investigate population growth rate:</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A modeling construct could be based upon laboratory toxicity tests to determine effect(s) that are then linked to the population model and used to estimate decline in population growth rate. Miller et al. (2007) used concentration–response data from short term reproductive assays with fathead minnow (<em>Pimephales promelas</em>) exposed to endocrine disrupting chemicals in combination with a population model to examine projected alterations in population growth rate. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A model construct could be based upon a combination of effects-based monitoring at field sites (informed by an AOP) and a population model. Miller et al. (2015) applied a population model informed by an AOP to project declines in population growth rate for white suckers (Catostomus commersoni) using observed changes in sex steroid synthesis in fish exposed to a complex pulp and paper mill effluent in Jackfish Bay, Ontario, Canada. Furthermore, a model construct could be comprised of a series of quantitative models using KERs that culminates in the estimation of change (decline) in population growth rate. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A quantitative adverse outcome pathway (qAOP) has been defined as a mathematical construct that models the dose–response or response–response relationships of all KERs described in an AOP (Conolly et al. 2017, Perkins et al. 2019). Conolly et al. (2017) developed a qAOP using data generated with the aromatase inhibitor fadrozole as a stressor and then used it to predict potential population‐level impacts (including decline in population growth rate). The qAOP modeled aromatase inhibition (the molecular initiating event) leading to reproductive dysfunction in fathead minnow (Pimephales promelas) using 3 computational models: a hypothalamus–pituitary–gonadal axis model (based on ordinary differential equations) of aromatase inhibition leading to decreased vitellogenin production (Cheng et al. 2016), a stochastic model of oocyte growth dynamics relating vitellogenin levels to clutch size and spawning intervals (Watanabe et al. 2016), and a population model (Miller et al. 2007).</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● Dynamic energy budget (DEB) models offer a methodology that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources (Nisbet et al. 2000, Nisbet et al. 2011). Murphy et al. (2018) developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates.</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● Endogenous Lifecycle Models (ELMs), capture the endogenous lifecycle processes of growth, development, survival, and reproduction and integrate these to estimate and predict expected fitness (Etterson and Ankley, 2021). AOPs can be used to inform ELMs of effects of chemical stressors on the vital rates that determine fitness, and to decide what hierarchical models of endogenous systems should be included within an ELM (Etterson and Ankley, 2021).</span></span></span></span></p>
<p> </p>
<br>
<h4>Regulatory Significance of the AO</h4>
<p>Maintenance of sustainable fish and wildlife populations (i.e., adequate to ensure long-term delivery of valued ecosystem services) is a widely accepted regulatory goal upon which risk assessments and risk management decisions are based.</p>
<h4>References</h4>
<ul>
<li>Miller DH, Ankley GT. 2004. Modeling impacts on populations: fathead minnow (Pimephales promelas) exposure to the endocrine disruptor 17ß-trenbolone as a case study. Ecotoxicology and Environmental Safety 59: 1-9.</li>
<h4>References</h4>
<ul>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Ankley GT, Jensen KM, Makynen EA, Kahl MD, Korte JJ, Hornung MW, Henry TR, Denny JS, Leino RL, Wilson VS, Cardon MD, Hartig PC, Gray LE. 2003. Effects of the androgenic growth promoter 17b-trenbolone on fecundity and reproductive endocrinology of the fathead minnow. Environ. Toxicol. Chem. 22: 1350–1360.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Bookhout TA. 1994. Research and management techniques for wildlife and habitats. The Wildlife Society, Bethesda, Maryland. 740 pp.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Cheng WY, Zhang Q, Schroeder A, Villeneuve DL, Ankley GT, Conolly R. 2016. Computational modeling of plasma vitellogenin alterations in response to aromatase inhibition in fathead minnows. Toxicol Sci 154: 78–89.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Conolly RB, Ankley GT, Cheng W-Y, Mayo ML, Miller DH, Perkins EJ, Villeneuve DL, Watanabe KH. 2017. Quantitative adverse outcome pathways and their application to predictive toxicology. Environ. Sci. Technol. 51: 4661-4672.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Etterson MA, Ankley GT. 2021. Endogenous Lifecycle Models for Chemical Risk Assessment. Environ. Sci. Technol. 55: 15596-15608. </span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Gotelli NJ, 2008. A Primer of Ecology. Sinauer Associates, Inc., Sunderland, MA, USA.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Holbech H, Kinnberg KL, Brande-Lavridsen N, Bjerregaard P, Petersen GI, Norrgren L, Orn S, Braunbeck T, Baumann L, Bomke C, Dorgerloh M, Bruns E, Ruehl-Fehlert C, Green JW, Springer TA, Gourmelon A. 2012 Comparison of zebrafish (<em>Danio rerio</em>) and fathead minnow <em>(Pimephales promelas</em>) as test species in the Fish Sexual Development Test (FSDT). Comp. Biochem. Physiol. C Toxicol. Pharmacol. 155: 407–415.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Kramer VJ, Etterson MA, Hecker M, Murphy CA, Roesijadi G, Spade DJ, Stromberg JA, Wang M, Ankley GT. </span><span style="color:black">2011. Adverse outcome pathways and risk assessment: Bridging to population level effects. Environ. Toxicol. Chem. 30, 64-76.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">McComb B, Zuckerberg B, Vesely D, Jordan C. 2021. Monitoring Animal Populations and their Habitats: A Practitioner's Guide. Pressbooks, Oregon State University, Corvallis, OR Version 1.13, 296 pp. </span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Miller DH, Villeneuve DL, Santana Rodriguez KJ, Ankley GT. 2022. A multidimensional matrix model for predicting the effect of male biased sex ratios on fish populations. Environmental Toxicology and Chemistry 41(4): 1066-1077.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Miller DH, Tietge JE, McMaster ME, Munkittrick KR, Xia X, Griesmer DA, Ankley GT. 2015. </span><span style="color:black">Linking mechanistic toxicology to population models in forecasting recovery from chemical stress: A case study from Jackfish Bay, Ontario, Canada. Environmental Toxicology and Chemistry 34(7): 1623-1633.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Miller DH, Jensen KM, Villeneuve DE, Kahl MD, Makynen EA, Durhan EJ, Ankley GT. 2007. </span><span style="color:black">Linkage of biochemical responses to population-level effects: A case study with vitellogenin in the fathead minnow (<em>Pimephales promelas</em>). Environ Toxicol Chem 26: 521–527.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Miller DH, Ankley GT. 2004. Modeling impacts on populations: Fathead minnow (<em>Pimephales promelas</em>) exposure to the endocrine disruptor 17b-trenbolone as a case study. Ecotox Environ Saf 59: 1–9.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Murphy CA, Nisbet RM, Antczak P, Garcia-Reyero N, Gergs A, Lika K, Mathews T, Muller EB, Nacci D, Peace A, Remien CH, Schultz IR, Stevenson LM, Watanabe KH. 2018. Incorporating suborganismal processes into dynamic energy budget models for ecological risk assessment. Integrated Environmental Assessment and Management 14(5): 615–624.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Murray DL, Sandercock BK (editors). 2020. Population ecology in practice. Wiley-Blackwell, Oxford UK, 448 pp.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Nisbet RM, Jusup M, Klanjscek T, Pecquerie L. 2011. Integrating dynamic energy budget (DEB) theory with traditional bioenergetic models. The Journal of Experimental Biology 215: 892-902.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Nisbet RM, Muller EB, Lika K, Kooijman SALM. 2000. </span><span style="color:black">From molecules to ecosystems through dynamic energy budgets. J Anim Ecol 69: 913–926.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Perkins EJ, Ashauer R, Burgoon L, Conolly R, Landesmann B,, Mackay C, Murphy CA, Pollesch N, Wheeler JR, Zupanic A, Scholzk S. 2019. Building and applying quantitative adverse outcome pathway models for chemical hazard and risk assessment. Environmental Toxicology and Chemistry 38(9): 1850–1865. </span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Vandermeer JH, Goldberg DE. 2003. Population ecology: first principles. Princeton University Press, Princeton NJ, 304 pp.</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Villeneuve DL, Crump D, Garcia-Reyero N, Hecker M, Hutchinson TH, LaLone CA, Landesmann B, Lattieri T, Munn S, Nepelska M, Ottinger MA, Vergauwen L, Whelan M. Adverse outcome pathway (AOP) development 1: Strategies and principles. Toxicol Sci. 2014: 142:312–320</span></span></span></li>
<li><span style="font-size:12pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">Watanabe KH, Mayo M, Jensen KM, Villeneuve DL, Ankley GT, Perkins EJ. 2016. Predicting fecundity of fathead minnows (<em>Pimephales promelas</em>) exposed to endocrine‐disrupting chemicals using a MATLAB(R)‐based model of oocyte growth dynamics. PLoS One 11: e0146594.</span></span></span></li>
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<!-- if nothing shows up in any of these fields, then evidence supporting this KER will not be displayed -->
<h4>Evidence Supporting this KER</h4>
<strong>Biological Plausibility</strong>
<p><em>
</div>
<div>
</div>
<div>
</div>
<h4>Evidence Supporting this KER</h4>
<strong>Biological Plausibility</strong>
<p><em>
High degree of plausibility in fathead minnow, zebrafish and other cyprinid species.
</em>
</p>
<strong>Empirical Evidence</strong>
<p><em>
<strong>Empirical Evidence</strong>
<p><em>
A wide range of studies using adult fish show that induction of plasma vitellogenin (VTG) occurs within 21 days in vivo aquatic exposure to estrogen receptor agonists (eg 17beta-estradiol and 4-tert pentylphenol) as shown during the successful validation of the OECD Test Guideline 229 and related protocols. A smaller number of experiment studies with fish have shown that within the OECD Test Guideline 2010, larval fish can also show induction of whole body VTG levels within 21 days aquatic exposure to estrogen receptor agonists.
</em>
</p>
<strong>Uncertainties and Inconsistencies</strong>
<p><em>
<strong>Uncertainties and Inconsistencies</strong>
<p><em>
There are generally few inconsistencies for experimental studies using model fish species dervied from pathogen-free laboratory cultures. However, there can some uncertainties where wild fish have been used for experimental purposes.
Navas, J.M., Segner, H. (2006) Vitellogenin synthesis in primary cultures of fish liver cells as endpoint for in vitro screening of the (anti)estrogenic activity of chemical substances. Aquatic Toxicology 80: 1-22
</p><p>Thorpe, K.L., Benstead, R., Hutchinson, T.H., Tyler, C.R. (2007). Associations between altered vitellogenin concentrations and adverse health effects in fathead minnow (Pimephales promelas). Aquatic Toxicology 85: 176-183
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<h4><a href="/relationships/254">Relationship: 254: Increase, Plasma vitellogenin concentrations leads to Increase, Renal pathology due to VTG deposition</a></h4>
<td><a href="/aops/29">Estrogen receptor agonism leading to reproductive dysfunction</a></td>
<td>adjacent</td>
<td>High</td>
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<th><a href="/aops/29">Estrogen receptor agonism leading to reproductive dysfunction</a></th>
<th>adjacent</th>
<th>High </th>
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<h4>Evidence Supporting Applicability of this Relationship</h4>
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<p><em>
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<h4>Evidence Supporting Applicability of this Relationship</h4>
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<p><em>
Publish studies specifically relate to fish, although it is plausible that the same response may occur in the aquatic life-stages of amphibians.
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<h4>Evidence Supporting this KER</h4>
<strong>Biological Plausibility</strong>
<p><em>
<h4>Evidence Supporting this KER</h4>
<strong>Biological Plausibility</strong>
<p><em>
High level of biological plausibility in fish.
</em>
</p>
<strong>Empirical Evidence</strong>
<p><em>
<strong>Empirical Evidence</strong>
<p><em>
Laboratory in vivo aquatic exposures of fish (fathead minnow) to 17alpha-ethinylestradiol led to renal pathology within 16 weeks, concomitant with macroscopic evidence of osmoregulatory dysfunction and morbidity (Laenge et al., 2001).
</em>
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<strong>Uncertainties and Inconsistencies</strong>
<p><em>
<strong>Uncertainties and Inconsistencies</strong>
<p>Herman, R.L., Kincaid, H.L. (1988) Pathological effects of orally administered 17beta-estradiol to rainbow trout. Aquaculture 72:165–172
<h4>References</h4>
<p>Herman, R.L., Kincaid, H.L. (1988) Pathological effects of orally administered 17beta-estradiol to rainbow trout. Aquaculture 72:165–172
</p><p>Länge, R., Hutchinson, T.H., Croudace, C.P., Siegmund, F., Schweinfurth, H., Hampe, P., Panter, G.H., Sumpter, J.P. (2001) Effects of the synthetic estrogen 17 alpha-ethinylestradiol on the life-cycle of the fathead minnow (Pimephales promelas). Environ Toxicol Chem 20:1216-1227