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<meta name="dcterms.date" content="2026-03-08">
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<title>Ecological Modelling Preregistration Template</title>
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<nav id="TOC" role="doc-toc" class="toc-active" data-toc-expanded="99">
<h2 id="toc-title">Table of contents</h2>
<ul>
<li><a href="#study-information" id="toc-study-information" class="nav-link active" data-scroll-target="#study-information">Study Information</a>
<ul class="collapse">
<li><a href="#credit-contribution-statement" id="toc-credit-contribution-statement" class="nav-link" data-scroll-target="#credit-contribution-statement">CRediT Contribution Statement</a></li>
<li><a href="#conflict-of-interest-statement" id="toc-conflict-of-interest-statement" class="nav-link" data-scroll-target="#conflict-of-interest-statement">Conflict of Interest Statement</a></li>
<li><a href="#data-availability-statement" id="toc-data-availability-statement" class="nav-link" data-scroll-target="#data-availability-statement">Data Availability Statement</a></li>
<li><a href="#code-availability" id="toc-code-availability" class="nav-link" data-scroll-target="#code-availability">Code Availability</a></li>
<li><a href="#ethics" id="toc-ethics" class="nav-link" data-scroll-target="#ethics">Ethics</a></li>
</ul></li>
<li><a href="#sec-problem-formulation" id="toc-sec-problem-formulation" class="nav-link" data-scroll-target="#sec-problem-formulation"><span class="header-section-number">1</span> Problem Formulation</a>
<ul class="collapse">
<li><a href="#model-context-and-purpose" id="toc-model-context-and-purpose" class="nav-link" data-scroll-target="#model-context-and-purpose"><span class="header-section-number">1.1</span> Model context and purpose</a>
<ul class="collapse">
<li><a href="#key-stakeholders-and-model-users" id="toc-key-stakeholders-and-model-users" class="nav-link" data-scroll-target="#key-stakeholders-and-model-users"><span class="header-section-number">1.1.1</span> Key stakeholders and model users</a></li>
<li><a href="#sec-model-purpose-context-and-problem-context" id="toc-sec-model-purpose-context-and-problem-context" class="nav-link" data-scroll-target="#sec-model-purpose-context-and-problem-context"><span class="header-section-number">1.1.2</span> Model purpose, context and problem context</a></li>
<li><a href="#sec-analytical-objectives" id="toc-sec-analytical-objectives" class="nav-link" data-scroll-target="#sec-analytical-objectives"><span class="header-section-number">1.1.3</span> Analytical objectives</a></li>
<li><a href="#logistical-constraints" id="toc-logistical-constraints" class="nav-link" data-scroll-target="#logistical-constraints"><span class="header-section-number">1.1.4</span> Logistical Constraints</a></li>
<li><a href="#model-scope-scale-and-resolution" id="toc-model-scope-scale-and-resolution" class="nav-link" data-scroll-target="#model-scope-scale-and-resolution"><span class="header-section-number">1.1.5</span> Model Scope, Scale and Resolution</a></li>
<li><a href="#intended-application-of-results" id="toc-intended-application-of-results" class="nav-link" data-scroll-target="#intended-application-of-results"><span class="header-section-number">1.1.6</span> Intended application of results</a></li>
</ul></li>
<li><a href="#scenario-analysis-operationalisation" id="toc-scenario-analysis-operationalisation" class="nav-link" data-scroll-target="#scenario-analysis-operationalisation"><span class="header-section-number">1.2</span> Scenario analysis operationalisation</a></li>
</ul></li>
<li><a href="#define-conceptual-model" id="toc-define-conceptual-model" class="nav-link" data-scroll-target="#define-conceptual-model"><span class="header-section-number">2</span> Define Conceptual Model</a>
<ul class="collapse">
<li><a href="#choose-elicitation-and-representation-method" id="toc-choose-elicitation-and-representation-method" class="nav-link" data-scroll-target="#choose-elicitation-and-representation-method"><span class="header-section-number">2.1</span> Choose elicitation and representation method</a></li>
<li><a href="#explain-critical-conceptual-design-decisions" id="toc-explain-critical-conceptual-design-decisions" class="nav-link" data-scroll-target="#explain-critical-conceptual-design-decisions"><span class="header-section-number">2.2</span> Explain critical conceptual design decisions</a></li>
<li><a href="#model-assumptions-and-uncertainties" id="toc-model-assumptions-and-uncertainties" class="nav-link" data-scroll-target="#model-assumptions-and-uncertainties"><span class="header-section-number">2.3</span> Model assumptions and uncertainties</a></li>
<li><a href="#identify-predictor-and-response-variables" id="toc-identify-predictor-and-response-variables" class="nav-link" data-scroll-target="#identify-predictor-and-response-variables"><span class="header-section-number">2.4</span> Identify predictor and response variables</a></li>
<li><a href="#define-prior-knowledge-data-specification-and-evaluation" id="toc-define-prior-knowledge-data-specification-and-evaluation" class="nav-link" data-scroll-target="#define-prior-knowledge-data-specification-and-evaluation"><span class="header-section-number">2.5</span> Define prior knowledge, data specification and evaluation</a>
<ul class="collapse">
<li><a href="#collate-available-data-sources-that-could-be-used-to-parameterise-or-structure-the-model" id="toc-collate-available-data-sources-that-could-be-used-to-parameterise-or-structure-the-model" class="nav-link" data-scroll-target="#collate-available-data-sources-that-could-be-used-to-parameterise-or-structure-the-model"><span class="header-section-number">2.5.1</span> Collate available data sources that could be used to parameterise or structure the model</a></li>
<li><a href="#data-processing-and-preparation" id="toc-data-processing-and-preparation" class="nav-link" data-scroll-target="#data-processing-and-preparation"><span class="header-section-number">2.5.2</span> Data Processing and Preparation</a></li>
<li><a href="#sec-exploratory-analyses" id="toc-sec-exploratory-analyses" class="nav-link" data-scroll-target="#sec-exploratory-analyses"><span class="header-section-number">2.5.3</span> Describe any data exploration or preliminary data analyses</a></li>
<li><a href="#data-evaluation-exclusion-and-missing-data" id="toc-data-evaluation-exclusion-and-missing-data" class="nav-link" data-scroll-target="#data-evaluation-exclusion-and-missing-data"><span class="header-section-number">2.5.4</span> Data evaluation, exclusion and missing data</a></li>
</ul></li>
<li><a href="#conceptual-model-evaluation" id="toc-conceptual-model-evaluation" class="nav-link" data-scroll-target="#conceptual-model-evaluation"><span class="header-section-number">2.6</span> Conceptual model evaluation</a></li>
</ul></li>
<li><a href="#formalise-and-specify-model" id="toc-formalise-and-specify-model" class="nav-link" data-scroll-target="#formalise-and-specify-model"><span class="header-section-number">3</span> Formalise and Specify Model</a>
<ul class="collapse">
<li><a href="#model-class-modelling-framework-and-approach" id="toc-model-class-modelling-framework-and-approach" class="nav-link" data-scroll-target="#model-class-modelling-framework-and-approach"><span class="header-section-number">3.1</span> Model class, modelling framework and approach</a></li>
<li><a href="#choose-model-features-and-family" id="toc-choose-model-features-and-family" class="nav-link" data-scroll-target="#choose-model-features-and-family"><span class="header-section-number">3.2</span> Choose model features and family</a>
<ul class="collapse">
<li><a href="#operationalising-model-variables" id="toc-operationalising-model-variables" class="nav-link" data-scroll-target="#operationalising-model-variables"><span class="header-section-number">3.2.1</span> Operationalising Model Variables</a></li>
<li><a href="#choose-model-family" id="toc-choose-model-family" class="nav-link" data-scroll-target="#choose-model-family"><span class="header-section-number">3.2.2</span> Choose model family</a></li>
</ul></li>
<li><a href="#describe-approach-for-identifying-model-structure" id="toc-describe-approach-for-identifying-model-structure" class="nav-link" data-scroll-target="#describe-approach-for-identifying-model-structure"><span class="header-section-number">3.3</span> Describe <em>approach</em> for identifying model structure</a></li>
<li><a href="#describe-parameter-estimation-technique-and-performance-criteria" id="toc-describe-parameter-estimation-technique-and-performance-criteria" class="nav-link" data-scroll-target="#describe-parameter-estimation-technique-and-performance-criteria"><span class="header-section-number">3.4</span> Describe parameter estimation technique and performance criteria</a>
<ul class="collapse">
<li><a href="#parameter-estimation-technique" id="toc-parameter-estimation-technique" class="nav-link" data-scroll-target="#parameter-estimation-technique"><span class="header-section-number">3.4.1</span> Parameter estimation technique</a></li>
<li><a href="#sec-parameter-model-fit-performance-criteria" id="toc-sec-parameter-model-fit-performance-criteria" class="nav-link" data-scroll-target="#sec-parameter-model-fit-performance-criteria"><span class="header-section-number">3.4.2</span> Parameter estimation / model fit performance criteria</a></li>
</ul></li>
<li><a href="#model-assumptions-and-uncertainties-1" id="toc-model-assumptions-and-uncertainties-1" class="nav-link" data-scroll-target="#model-assumptions-and-uncertainties-1"><span class="header-section-number">3.5</span> Model assumptions and uncertainties</a></li>
<li><a href="#specify-formal-models" id="toc-specify-formal-models" class="nav-link" data-scroll-target="#specify-formal-models"><span class="header-section-number">3.6</span> Specify formal model(s)</a></li>
</ul></li>
<li><a href="#model-calibration-validation-checking" id="toc-model-calibration-validation-checking" class="nav-link" data-scroll-target="#model-calibration-validation-checking"><span class="header-section-number">4</span> Model Calibration, Validation & Checking</a>
<ul class="collapse">
<li><a href="#model-calibration-and-validation-scheme" id="toc-model-calibration-and-validation-scheme" class="nav-link" data-scroll-target="#model-calibration-and-validation-scheme"><span class="header-section-number">4.1</span> Model calibration and validation scheme</a>
<ul class="collapse">
<li><a href="#sec-calibration-data" id="toc-sec-calibration-data" class="nav-link" data-scroll-target="#sec-calibration-data"><span class="header-section-number">4.1.1</span> Describe calibration/validation data</a></li>
</ul></li>
<li><a href="#implementation-verification" id="toc-implementation-verification" class="nav-link" data-scroll-target="#implementation-verification"><span class="header-section-number">4.2</span> Implementation verification</a></li>
<li><a href="#model-checking" id="toc-model-checking" class="nav-link" data-scroll-target="#model-checking"><span class="header-section-number">4.3</span> Model checking</a>
<ul class="collapse">
<li><a href="#quantitative-model-checking" id="toc-quantitative-model-checking" class="nav-link" data-scroll-target="#quantitative-model-checking"><span class="header-section-number">4.3.1</span> Quantitative model checking</a></li>
<li><a href="#qualitative-model-checking" id="toc-qualitative-model-checking" class="nav-link" data-scroll-target="#qualitative-model-checking"><span class="header-section-number">4.3.2</span> Qualitative model checking</a></li>
<li><a href="#assumption-violation-checks" id="toc-assumption-violation-checks" class="nav-link" data-scroll-target="#assumption-violation-checks"><span class="header-section-number">4.3.3</span> Assumption Violation Checks</a></li>
</ul></li>
</ul></li>
<li><a href="#model-validation-and-evaluation" id="toc-model-validation-and-evaluation" class="nav-link" data-scroll-target="#model-validation-and-evaluation"><span class="header-section-number">5</span> Model Validation and Evaluation</a>
<ul class="collapse">
<li><a href="#model-output-corroboration" id="toc-model-output-corroboration" class="nav-link" data-scroll-target="#model-output-corroboration"><span class="header-section-number">5.1</span> Model output corroboration</a></li>
<li><a href="#choose-performance-metrics-and-criteria" id="toc-choose-performance-metrics-and-criteria" class="nav-link" data-scroll-target="#choose-performance-metrics-and-criteria"><span class="header-section-number">5.2</span> Choose performance metrics and criteria</a></li>
<li><a href="#model-analysis" id="toc-model-analysis" class="nav-link" data-scroll-target="#model-analysis"><span class="header-section-number">5.3</span> Model analysis</a>
<ul class="collapse">
<li><a href="#uncertainty-analyses" id="toc-uncertainty-analyses" class="nav-link" data-scroll-target="#uncertainty-analyses"><span class="header-section-number">5.3.1</span> Uncertainty Analyses</a></li>
<li><a href="#sensitivity-analyses" id="toc-sensitivity-analyses" class="nav-link" data-scroll-target="#sensitivity-analyses"><span class="header-section-number">5.3.2</span> Sensitivity analyses</a></li>
<li><a href="#model-application-or-scenario-analysis" id="toc-model-application-or-scenario-analysis" class="nav-link" data-scroll-target="#model-application-or-scenario-analysis"><span class="header-section-number">5.3.3</span> Model application or scenario analysis</a></li>
<li><a href="#other-simulation-experiments-robustness-analyses" id="toc-other-simulation-experiments-robustness-analyses" class="nav-link" data-scroll-target="#other-simulation-experiments-robustness-analyses"><span class="header-section-number">5.3.4</span> Other simulation experiments / robustness analyses</a></li>
</ul></li>
</ul></li>
<li><a href="#references" id="toc-references" class="nav-link" data-scroll-target="#references">References</a></li>
</ul>
<div class="quarto-alternate-formats"><h2>Other Formats</h2><ul><li><a href="template.pdf"><i class="bi bi-file-pdf"></i>PDF (ecoconsmodprereg)</a></li><li><a href="template.docx"><i class="bi bi-file-word"></i>MS Word (ecoconsmodprereg)</a></li></ul></div></nav>
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<main class="content" id="quarto-document-content">
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<h1 class="title">Ecological Modelling Preregistration Template</h1>
</div>
<div class="quarto-title-meta-author">
<div class="quarto-title-meta-heading">Authors</div>
<div class="quarto-title-meta-heading">Affiliations</div>
<div class="quarto-title-meta-contents">
<p class="author"><a href="https://github.com/egouldo">Elliot Gould</a> <a href="mailto:elliot.gould@unimelb.edu.au" class="quarto-title-author-email"><i class="bi bi-envelope"></i></a> <a href="https://orcid.org/0000-0002-6585-538X" class="quarto-title-author-orcid"> <img src="data:image/png;base64,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"></a></p>
</div>
<div class="quarto-title-meta-contents">
<p class="affiliation">
School of Agriculture, Food and Ecosystem Sciences, University of Melbourne
</p>
</div>
<div class="quarto-title-meta-contents">
<p class="author">Christopher S. Jones <a href="https://orcid.org/0000-0003-2833-0194" class="quarto-title-author-orcid"> <img src="data:image/png;base64,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"></a></p>
</div>
<div class="quarto-title-meta-contents">
<p class="affiliation">
School of Agriculture, Food and Ecosystem Sciences, University of Melbourne
</p>
<p class="affiliation">
Arthur Rylah Institute for Environmental Research, Department of Energy, Environment and Climate Action
</p>
</div>
<div class="quarto-title-meta-contents">
<p class="author">Jian D.L. Yen <a href="https://orcid.org/0000-0001-7964-923X" class="quarto-title-author-orcid"> <img src="data:image/png;base64,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"></a></p>
</div>
<div class="quarto-title-meta-contents">
<p class="affiliation">
Arthur Rylah Institute for Environmental Research, Department of Energy, Environment and Climate Action
</p>
</div>
<div class="quarto-title-meta-contents">
<p class="author">Hannah S. Fraser <a href="https://orcid.org/0000-0003-2443-4463" class="quarto-title-author-orcid"> <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAA2ZpVFh0WE1MOmNvbS5hZG9iZS54bXAAAAAAADw/eHBhY2tldCBiZWdpbj0i77u/IiBpZD0iVzVNME1wQ2VoaUh6cmVTek5UY3prYzlkIj8+IDx4OnhtcG1ldGEgeG1sbnM6eD0iYWRvYmU6bnM6bWV0YS8iIHg6eG1wdGs9IkFkb2JlIFhNUCBDb3JlIDUuMC1jMDYwIDYxLjEzNDc3NywgMjAxMC8wMi8xMi0xNzozMjowMCAgICAgICAgIj4gPHJkZjpSREYgeG1sbnM6cmRmPSJodHRwOi8vd3d3LnczLm9yZy8xOTk5LzAyLzIyLXJkZi1zeW50YXgtbnMjIj4gPHJkZjpEZXNjcmlwdGlvbiByZGY6YWJvdXQ9IiIgeG1sbnM6eG1wTU09Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC9tbS8iIHhtbG5zOnN0UmVmPSJodHRwOi8vbnMuYWRvYmUuY29tL3hhcC8xLjAvc1R5cGUvUmVzb3VyY2VSZWYjIiB4bWxuczp4bXA9Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8iIHhtcE1NOk9yaWdpbmFsRG9jdW1lbnRJRD0ieG1wLmRpZDo1N0NEMjA4MDI1MjA2ODExOTk0QzkzNTEzRjZEQTg1NyIgeG1wTU06RG9jdW1lbnRJRD0ieG1wLmRpZDozM0NDOEJGNEZGNTcxMUUxODdBOEVCODg2RjdCQ0QwOSIgeG1wTU06SW5zdGFuY2VJRD0ieG1wLmlpZDozM0NDOEJGM0ZGNTcxMUUxODdBOEVCODg2RjdCQ0QwOSIgeG1wOkNyZWF0b3JUb29sPSJBZG9iZSBQaG90b3Nob3AgQ1M1IE1hY2ludG9zaCI+IDx4bXBNTTpEZXJpdmVkRnJvbSBzdFJlZjppbnN0YW5jZUlEPSJ4bXAuaWlkOkZDN0YxMTc0MDcyMDY4MTE5NUZFRDc5MUM2MUUwNEREIiBzdFJlZjpkb2N1bWVudElEPSJ4bXAuZGlkOjU3Q0QyMDgwMjUyMDY4MTE5OTRDOTM1MTNGNkRBODU3Ii8+IDwvcmRmOkRlc2NyaXB0aW9uPiA8L3JkZjpSREY+IDwveDp4bXBtZXRhPiA8P3hwYWNrZXQgZW5kPSJyIj8+84NovQAAAR1JREFUeNpiZEADy85ZJgCpeCB2QJM6AMQLo4yOL0AWZETSqACk1gOxAQN+cAGIA4EGPQBxmJA0nwdpjjQ8xqArmczw5tMHXAaALDgP1QMxAGqzAAPxQACqh4ER6uf5MBlkm0X4EGayMfMw/Pr7Bd2gRBZogMFBrv01hisv5jLsv9nLAPIOMnjy8RDDyYctyAbFM2EJbRQw+aAWw/LzVgx7b+cwCHKqMhjJFCBLOzAR6+lXX84xnHjYyqAo5IUizkRCwIENQQckGSDGY4TVgAPEaraQr2a4/24bSuoExcJCfAEJihXkWDj3ZAKy9EJGaEo8T0QSxkjSwORsCAuDQCD+QILmD1A9kECEZgxDaEZhICIzGcIyEyOl2RkgwAAhkmC+eAm0TAAAAABJRU5ErkJggg=="></a></p>
</div>
<div class="quarto-title-meta-contents">
<p class="affiliation">
School of Agriculture, Food and Ecosystem Sciences, University of Melbourne
</p>
</div>
<div class="quarto-title-meta-contents">
<p class="author">Henry Wootton <a href="https://orcid.org/0000-0001-6506-0248" class="quarto-title-author-orcid"> <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAA2ZpVFh0WE1MOmNvbS5hZG9iZS54bXAAAAAAADw/eHBhY2tldCBiZWdpbj0i77u/IiBpZD0iVzVNME1wQ2VoaUh6cmVTek5UY3prYzlkIj8+IDx4OnhtcG1ldGEgeG1sbnM6eD0iYWRvYmU6bnM6bWV0YS8iIHg6eG1wdGs9IkFkb2JlIFhNUCBDb3JlIDUuMC1jMDYwIDYxLjEzNDc3NywgMjAxMC8wMi8xMi0xNzozMjowMCAgICAgICAgIj4gPHJkZjpSREYgeG1sbnM6cmRmPSJodHRwOi8vd3d3LnczLm9yZy8xOTk5LzAyLzIyLXJkZi1zeW50YXgtbnMjIj4gPHJkZjpEZXNjcmlwdGlvbiByZGY6YWJvdXQ9IiIgeG1sbnM6eG1wTU09Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC9tbS8iIHhtbG5zOnN0UmVmPSJodHRwOi8vbnMuYWRvYmUuY29tL3hhcC8xLjAvc1R5cGUvUmVzb3VyY2VSZWYjIiB4bWxuczp4bXA9Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8iIHhtcE1NOk9yaWdpbmFsRG9jdW1lbnRJRD0ieG1wLmRpZDo1N0NEMjA4MDI1MjA2ODExOTk0QzkzNTEzRjZEQTg1NyIgeG1wTU06RG9jdW1lbnRJRD0ieG1wLmRpZDozM0NDOEJGNEZGNTcxMUUxODdBOEVCODg2RjdCQ0QwOSIgeG1wTU06SW5zdGFuY2VJRD0ieG1wLmlpZDozM0NDOEJGM0ZGNTcxMUUxODdBOEVCODg2RjdCQ0QwOSIgeG1wOkNyZWF0b3JUb29sPSJBZG9iZSBQaG90b3Nob3AgQ1M1IE1hY2ludG9zaCI+IDx4bXBNTTpEZXJpdmVkRnJvbSBzdFJlZjppbnN0YW5jZUlEPSJ4bXAuaWlkOkZDN0YxMTc0MDcyMDY4MTE5NUZFRDc5MUM2MUUwNEREIiBzdFJlZjpkb2N1bWVudElEPSJ4bXAuZGlkOjU3Q0QyMDgwMjUyMDY4MTE5OTRDOTM1MTNGNkRBODU3Ii8+IDwvcmRmOkRlc2NyaXB0aW9uPiA8L3JkZjpSREY+IDwveDp4bXBtZXRhPiA8P3hwYWNrZXQgZW5kPSJyIj8+84NovQAAAR1JREFUeNpiZEADy85ZJgCpeCB2QJM6AMQLo4yOL0AWZETSqACk1gOxAQN+cAGIA4EGPQBxmJA0nwdpjjQ8xqArmczw5tMHXAaALDgP1QMxAGqzAAPxQACqh4ER6uf5MBlkm0X4EGayMfMw/Pr7Bd2gRBZogMFBrv01hisv5jLsv9nLAPIOMnjy8RDDyYctyAbFM2EJbRQw+aAWw/LzVgx7b+cwCHKqMhjJFCBLOzAR6+lXX84xnHjYyqAo5IUizkRCwIENQQckGSDGY4TVgAPEaraQr2a4/24bSuoExcJCfAEJihXkWDj3ZAKy9EJGaEo8T0QSxkjSwORsCAuDQCD+QILmD1A9kECEZgxDaEZhICIzGcIyEyOl2RkgwAAhkmC+eAm0TAAAAABJRU5ErkJggg=="></a></p>
</div>
<div class="quarto-title-meta-contents">
<p class="affiliation">
Arthur Rylah Institute for Environmental Research, Department of Energy, Environment and Climate Action
</p>
</div>
<div class="quarto-title-meta-contents">
<p class="author">Megan K. Good <a href="https://orcid.org/0000-0002-6908-1633" class="quarto-title-author-orcid"> <img src="data:image/png;base64,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"></a></p>
</div>
<div class="quarto-title-meta-contents">
<p class="affiliation">
School of Agriculture, Food and Ecosystem Sciences, University of Melbourne
</p>
</div>
<div class="quarto-title-meta-contents">
<p class="author">David H. Duncan <a href="https://orcid.org/0000-0003-4411-8214" class="quarto-title-author-orcid"> <img src="data:image/png;base64,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"></a></p>
</div>
<div class="quarto-title-meta-contents">
<p class="affiliation">
School of Agriculture, Food and Ecosystem Sciences, University of Melbourne
</p>
</div>
<div class="quarto-title-meta-contents">
<p class="author">Cindy E. Hauser <a href="https://orcid.org/0000-0002-5187-6585" class="quarto-title-author-orcid"> <img src="data:image/png;base64,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"></a></p>
</div>
<div class="quarto-title-meta-contents">
<p class="affiliation">
Arthur Rylah Institute for Environmental Research, Department of Energy, Environment and Climate Action
</p>
</div>
<div class="quarto-title-meta-contents">
<p class="author">Bonnie C. Wintle <a href="https://orcid.org/0000-0001-9400-8086" class="quarto-title-author-orcid"> <img src="data:image/png;base64,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"></a></p>
</div>
<div class="quarto-title-meta-contents">
<p class="affiliation">
School of Agriculture, Food and Ecosystem Sciences, University of Melbourne
</p>
</div>
<div class="quarto-title-meta-contents">
<p class="author">Libby Rumpff <a href="https://orcid.org/0000-0001-9400-8086" class="quarto-title-author-orcid"> <img src="data:image/png;base64,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"></a></p>
</div>
<div class="quarto-title-meta-contents">
<p class="affiliation">
School of Agriculture, Food and Ecosystem Sciences, University of Melbourne
</p>
</div>
</div>
<div class="quarto-title-meta">
<div>
<div class="quarto-title-meta-heading">Published</div>
<div class="quarto-title-meta-contents">
<p class="date">March 8, 2026</p>
</div>
</div>
</div>
<div>
<div class="abstract">
<div class="block-title">Background and Instructions</div>
<p>Here we present a preregistration template for ecological models in ecology, conservation and related fields.</p>
<p>Replace author, author-affiliations and persistent ID’s (e.g. <a href="https://orcid.org/">ORCID iD</a>), keywords, title and abstract <a href="https://quarto.org/docs/journals/authors.html">metadata in the document YAML</a> as relevant to your study.</p>
<p>For non-trivial modelling studies, especially where model parameter and structure is in any way data-contingent, we recommend taking an <em><a href="https://egouldo.github.io/EcoConsPreReg/">Adaptive Preregistration</a></em> approach <span class="citation" data-cites="Gould2024a">(<a href="#ref-Gould2024a" role="doc-biblioref">Gould et al., 2024</a>)</span>. Please read the <a href="https://egouldo.github.io/EcoConsPreReg/adaptive_preregistration_background.html"><em>Primer on Adaptive Preregistration</em></a> before beginning.</p>
<p>All preregistration items should be completed, excluding items marked as optional or in cases where they are not applicable to your study, which can be deleted. Additional preregistration items can be added as required at the researchers’ discretion.</p>
</div>
</div>
<div>
<div class="keywords">
<div class="block-title">Keywords</div>
<p>preregistration, preregistration template, transparency, reproducibility, open-science</p>
</div>
</div>
</header>
<section id="study-information" class="level1 unnumbered">
<h1 class="unnumbered">Study Information</h1>
<section id="credit-contribution-statement" class="level2 unnumbered">
<h2 class="unnumbered anchored" data-anchor-id="credit-contribution-statement">CRediT Contribution Statement</h2>
<div class="callout callout-style-default callout-caution callout-titled">
<div class="callout-header d-flex align-content-center">
<div class="callout-icon-container">
<i class="callout-icon"></i>
</div>
<div class="callout-title-container flex-fill">
<span class="screen-reader-only">Caution</span>Preregistration Item
</div>
</div>
<div class="callout-body-container callout-body">
<p>Identify potential contributions according to the CRediT taxonomy (<a href="https://doi.org/10.1371/journal.pone.0244611.t001" class="uri">https://doi.org/10.1371/journal.pone.0244611.t001</a>) and write a <a href="https://authorservices.wiley.com/author-resources/Journal-Authors/open-access/credit.html" title="See link for example statement.">CRediT contribution statement</a>.</p>
</div>
</div>
</section>
<section id="conflict-of-interest-statement" class="level2 unnumbered">
<h2 class="unnumbered anchored" data-anchor-id="conflict-of-interest-statement">Conflict of Interest Statement</h2>
<div class="callout callout-style-default callout-caution callout-titled">
<div class="callout-header d-flex align-content-center">
<div class="callout-icon-container">
<i class="callout-icon"></i>
</div>
<div class="callout-title-container flex-fill">
<span class="screen-reader-only">Caution</span>Preregistration Item
</div>
</div>
<div class="callout-body-container callout-body">
<ul class="task-list">
<li><label><input type="checkbox">Explain any real or perceived conflicts of interest with this study execution. For example, any interests or activities that might be seen as influencing the research (e.g., financial interests in a test or procedure, funding by companies for research).</label></li>
</ul>
</div>
</div>
</section>
<section id="data-availability-statement" class="level2 unnumbered">
<h2 class="unnumbered anchored" data-anchor-id="data-availability-statement">Data Availability Statement</h2>
<div class="callout callout-style-default callout-caution callout-titled">
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<p><em>Select one option from below:</em></p>
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<li><label><input type="checkbox">“We plan to make the data available (yes / no),” specify the planned data availability level from the following options:</label>
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<li>Data access via download; usage of data for all purposes (public use file)</li>
<li>Data access via download; usage of data restricted to scientific purposes (scientific use file)</li>
<li>Data access via download; usage of data has to be agreed and defined on an individual case basis</li>
<li>Data access via secure data centre (no download, usage/analysis only in a secure data centre)</li>
<li>Data available upon email request by member of scientific community</li>
<li>Other (please specify)</li>
</ul></li>
<li><label><input type="checkbox">“Data will not be made available”</label>
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<li><label><input type="checkbox">Justify reason for not making data available.</label></li>
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</section>
<section id="code-availability" class="level2 unnumbered">
<h2 class="unnumbered anchored" data-anchor-id="code-availability">Code Availability</h2>
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<p><em>Select one option from below:</em></p>
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<li><label><input type="checkbox">“We plan to make the code available (yes / no),” specify the planned code availability level from the following options:</label>
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<li>Code access via download; usage of code for all purposes (public use file)</li>
<li>Code access via download; usage of code restricted to scientific purposes (scientific use file)</li>
<li>Code access via download; usage of code has to be agreed and defined on an individual case basis</li>
<li>Code access via secure code centre (no download, usage/analysis only in a secure code centre)</li>
<li>Code available upon email request by member of scientific community</li>
<li>Other (please specify)</li>
</ul></li>
<li><label><input type="checkbox">“Code will not be made available”</label>
<ul class="task-list">
<li><label><input type="checkbox">Justify reason for not making code available.</label></li>
</ul></li>
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</section>
<section id="ethics" class="level2 unnumbered">
<h2 class="unnumbered anchored" data-anchor-id="ethics">Ethics</h2>
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<li><label><input type="checkbox">Select and respond to the relevant item below:</label>
<ul>
<li>If relevant institutional ethical approval for the study has been obtained, provide the relevant identifier, and link to relevant documents.</li>
<li>If ethical approval has not yet been obtained, but is required, provide a brief overview of plans for obtaining study approval in accordance with established ethical guidelines.</li>
<li>Alternatively, if the study is exempt from ethical approval, explain exemption.</li>
</ul></li>
</ul>
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</div>
</section>
</section>
<section id="sec-problem-formulation" class="level1" data-number="1">
<h1 data-number="1"><span class="header-section-number">1</span> Problem Formulation</h1>
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<p>This section specifies the decision-making context in which the model will be used or the intended scope and context of conclusions. Important components include the decision maker and stakeholders (including experts) and their view on: i) the nature of the problem or decision addressed and how the scope of the modelling tool fits within the (broader) context (i.e. model purpose; ii) the spatial and temporal scales relevant to the decision context; iii) specified desired outputs; iv) role and inclusion in model development and testing; v) whether they foresee unacceptable outcomes that need to be represented in the model (i.e. as constraints), and; vi) what future scenarios does the model need to account for (noting this may be revised later). It should also provide a summary of the domain of applicability of the model, and reasonable extrapolation limits <span class="citation" data-cites="Grimm:2014es">(<a href="#ref-Grimm:2014es" role="doc-biblioref">Grimm et al., 2014</a>)</span>.</p>
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<section id="model-context-and-purpose" class="level2" data-number="1.1">
<h2 data-number="1.1" class="anchored" data-anchor-id="model-context-and-purpose"><span class="header-section-number">1.1</span> Model context and purpose</h2>
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<p>Defining the purpose of the model is critical because the model purpose influences choices at later stages of model development <span class="citation" data-cites="Jakeman:2006ii">(<a href="#ref-Jakeman:2006ii" role="doc-biblioref">Jakeman et al., 2006</a>)</span>. Common model purposes in ecology include: gaining a better qualitative understanding of the target system, synthesising and reviewing knowledge, and providing guidance for management and decision-making <span class="citation" data-cites="Jakeman:2006ii">(<a href="#ref-Jakeman:2006ii" role="doc-biblioref">Jakeman et al., 2006</a>)</span>. Note that modelling objectives are distinct from the analytical objectives of the model.</p>
<p>The scope of the model includes temporal and spatial resolutions, which should also be defined here <span class="citation" data-cites="Mahmoud2009">(<a href="#ref-Mahmoud2009" role="doc-biblioref">Mahmoud et al., 2009</a>)</span>. Any external limitations on model development, analysis and flexibility should also be outlined in this section <span class="citation" data-cites="Jakeman:2006ii">(<a href="#ref-Jakeman:2006ii" role="doc-biblioref">Jakeman et al., 2006</a>)</span>.</p>
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<section id="key-stakeholders-and-model-users" class="level3" data-number="1.1.1">
<h3 data-number="1.1.1" class="anchored" data-anchor-id="key-stakeholders-and-model-users"><span class="header-section-number">1.1.1</span> Key stakeholders and model users</h3>
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<p><em>Identify relevant interest groups:</em></p>
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<li><label><input type="checkbox">Who is the model for?</label></li>
<li><label><input type="checkbox">Who is involved in formulating the model?</label></li>
<li><label><input type="checkbox">How will key stakeholders be involved in model development?</label></li>
<li><label><input type="checkbox">Describe the decision-making context in which the model will be used (if relevant).</label></li>
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<section id="sec-model-purpose-context-and-problem-context" class="level3" data-number="1.1.2">
<h3 data-number="1.1.2" class="anchored" data-anchor-id="sec-model-purpose-context-and-problem-context"><span class="header-section-number">1.1.2</span> Model purpose, context and problem context</h3>
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<p><em>Briefly outline:</em></p>
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<li><label><input type="checkbox">the ecological problem,</label></li>
<li><label><input type="checkbox">the decision problem (if relevant), including the decision-trigger and any regulatory frameworks relevant to the problem,</label></li>
<li><label><input type="checkbox">how the model will address the problem, being clear about the scope of the model i.e. is the model addressing the whole problem, or part of it? Are there any linked problems that your model should consider?</label></li>
<li><label><input type="checkbox">Ensure that you specify any focal taxa and study objectives.</label></li>
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</section>
<section id="sec-analytical-objectives" class="level3" data-number="1.1.3">
<h3 data-number="1.1.3" class="anchored" data-anchor-id="sec-analytical-objectives"><span class="header-section-number">1.1.3</span> Analytical objectives</h3>
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<p>How will the model be analysed, what analytical questions will the model be used to answer? For example, you might be using your model in a scenario analysis to determine which management decision is associated with minimum regret or the highest likelihood of improvement. Other examples from ecological decision-making include: to compare the performance of alternative management actions under budget constraint <span class="citation" data-cites="Fraser:2017jf">(<a href="#ref-Fraser:2017jf" role="doc-biblioref">Fraser et al., 2017</a>)</span>, to search for robust decisions under uncertainty <span class="citation" data-cites="McDonald-Madden2008">(<a href="#ref-McDonald-Madden2008" role="doc-biblioref">McDonald-Madden et al., 2008</a>)</span>, to choose the conservation policy that minimises uncertainty <span class="citation" data-cites="McCarthy2011">(<a href="#ref-McCarthy2011" role="doc-biblioref">McCarthy et al., 2011</a>)</span>. See other examples in <span class="citation" data-cites="Moallemi2019">(<a href="#ref-Moallemi2019" role="doc-biblioref">Moallemi et al., 2019</a>)</span>.</p>
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<p><em>Provide detail on the analytical purpose and scope of the model:</em></p>
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<li><label><input type="checkbox">How will the model be analysed and what analytical questions will the model be used to answer?</label></li>
<li><label><input type="checkbox">Candidate decisions should be investigated and are specified a priori. Depending on the modelling context, they may be specified by stakeholders, model users or the analyst <span class="citation" data-cites="Moallemi2019">(<a href="#ref-Moallemi2019" role="doc-biblioref">Moallemi et al., 2019</a>)</span>.</label>
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<li><label><input type="checkbox">Describe the method used to identify relevant management actions and</label></li>
<li><label><input type="checkbox">specify management actions to be considered included in the model.</label></li>
<li><label><input type="checkbox">Are there potentially unacceptable management or policy outcomes identified by stakeholders that should be captured in the model, i.e. as constraints?</label></li>
</ul></li>
<li><label><input type="checkbox">Are there scenarios that model inputs or outputs that must accommodated? Scenarios should be set a priori, <span class="citation" data-cites="Moallemi2019">(i.e. before the model is built, <a href="#ref-Moallemi2019" role="doc-biblioref">Moallemi et al., 2019</a>)</span> and may be stakeholder-defined or driven by the judgement of the modeller or other experts <span class="citation" data-cites="Mahmoud2009">(<a href="#ref-Mahmoud2009" role="doc-biblioref">Mahmoud et al., 2009</a>)</span>.</label>
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<li><label><input type="checkbox">If relevant, describe what processes you will use to elicit and identify relevant scenarios, e.g. literature review, structured workshops with stakeholders or decision-makers.</label></li>
<li><label><input type="checkbox">Specify scenarios under which decisions are investigated.</label></li>
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<section id="logistical-constraints" class="level3" data-number="1.1.4">
<h3 data-number="1.1.4" class="anchored" data-anchor-id="logistical-constraints"><span class="header-section-number">1.1.4</span> Logistical Constraints</h3>
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<li><label><input type="checkbox">What degree of flexibility is required from the model? Might the model need to be quickly reconfigured to explore new scenarios or problems proposed by clients / managers / model-users?</label></li>
<li><label><input type="checkbox">Are there any limitations on model development analysis and flexibility, such as time or budget constraints, for example, does a model need to be deployed rapidly?</label>
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<li><label><input type="checkbox">When must the model be completed by, e.g. to help make a decision?</label></li>
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<section id="model-scope-scale-and-resolution" class="level3" data-number="1.1.5">
<h3 data-number="1.1.5" class="anchored" data-anchor-id="model-scope-scale-and-resolution"><span class="header-section-number">1.1.5</span> Model Scope, Scale and Resolution</h3>
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<li><label><input type="checkbox">The choice of a model’s boundaries is closely linked to the choice of how finely to aggregate the behaviour within the model <span class="citation" data-cites="Jakeman:2006ii">(<a href="#ref-Jakeman:2006ii" role="doc-biblioref">Jakeman et al., 2006</a>)</span> - what is the intended scale, and resolution of the model (temporal, spatial or otherwise)?</label></li>
<li><label><input type="checkbox">Where is the boundary of the modelled system? Everything outside beyond the boundary and not crossing it is to be ignored within the domain of the model, and everything crossing the boundary is to be treated as external forcing (known/unknown), or else as model outputs <span class="citation" data-cites="Jakeman:2006ii">(observed, or not, <a href="#ref-Jakeman:2006ii" role="doc-biblioref">Jakeman et al., 2006</a>)</span>.</label></li>
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<section id="intended-application-of-results" class="level3" data-number="1.1.6">
<h3 data-number="1.1.6" class="anchored" data-anchor-id="intended-application-of-results"><span class="header-section-number">1.1.6</span> Intended application of results</h3>
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<p>Preregistration Items in this section are relevant to model transferability <span class="citation" data-cites="Yates2018">(<a href="#ref-Yates2018" role="doc-biblioref">Yates et al., 2018</a>)</span> and constraints on generality in model analysis interpretation. How far do can the results be extrapolated based on the study design (data + model + analysis)? For instance, if there are many confounding variables and not enough spatial / environmental replication, then making broader more general claims beyond the stated boundaries of the model (<a href="#sec-analytical-objectives" class="quarto-xref">Section 1.1.3</a>) may not be warranted. However, larger generalisations about results may be acceptable if the data comes from experimentally manipulated or controlled systems.</p>
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<li><label><input type="checkbox">What is the intended domain in which the model is to be applied? Are there any reasonable extrapolation limits beyond which you expect the model should not be applied <span class="citation" data-cites="Grimm:2014es">(<a href="#ref-Grimm:2014es" role="doc-biblioref">Grimm et al., 2014</a>)</span>?</label></li>
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<section id="scenario-analysis-operationalisation" class="level2" data-number="1.2">
<h2 data-number="1.2" class="anchored" data-anchor-id="scenario-analysis-operationalisation"><span class="header-section-number">1.2</span> Scenario analysis operationalisation</h2>
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<li><label><input type="checkbox">How will you operationalise any scenarios identified in <a href="#sec-analytical-objectives" class="quarto-xref">Section 1.1.3</a>? For example, how will you operationalise any qualitative changes of interest, such as ‚ ‘deterioration’ or ‘improvement’?</label></li>
<li><label><input type="checkbox">Describe how you will evaluate and distinguish the performance of alternative scenario outcomes</label></li>
<li><label><input type="checkbox">Justify or otherwise explain how you chose these measures and determined performance criteria in relation to the analytical objectives, model purpose and modelling context, such as the risk attitudes of decision-makers and stakeholders within this system</label></li>
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<section id="define-conceptual-model" class="level1" data-number="2">
<h1 data-number="2"><span class="header-section-number">2</span> Define Conceptual Model</h1>
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<p>Conceptual models underpin the formal or quantitative model <span class="citation" data-cites="Cartwright:2016kr">(<a href="#ref-Cartwright:2016kr" role="doc-biblioref">Cartwright et al., 2016</a>)</span>. The conceptual model describes the biological mechanisms relevant to the ecological problem and should capture basic premises about how the target system works, including any prior knowledge and assumptions about system processes. Conceptual models may be represented in a variety of formats, such as influence diagrams, linguistic model block diagram or bond graphs, and these illustrate how model drivers are linked to both outputs or observed responses, and internal (state) variables <span class="citation" data-cites="Jakeman:2006ii">(<a href="#ref-Jakeman:2006ii" role="doc-biblioref">Jakeman et al., 2006</a>)</span>.</p>
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<section id="choose-elicitation-and-representation-method" class="level2" data-number="2.1">
<h2 data-number="2.1" class="anchored" data-anchor-id="choose-elicitation-and-representation-method"><span class="header-section-number">2.1</span> Choose elicitation and representation method</h2>
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<li><label><input type="checkbox">Describe what method you will use to elicit or identify the conceptual model. Some common methods include interviews, drawings, and mapping techniques including influence diagrams, cognitive maps and Bayesian belief networks <span class="citation" data-cites="Moon2019">(<a href="#ref-Moon2019" role="doc-biblioref">Moon et al., 2019</a>)</span>. It is difficult to decide and justify which method is most appropriate, see Moon et al. <span class="citation" data-cites="Moon2019">(<a href="#ref-Moon2019" role="doc-biblioref">2019</a>)</span> for guidance addressing this methodological question.</label></li>
<li><label><input type="checkbox">Finally, how do you intend on representing the final conceptual model? This will likely depend on the method chosen to elicit the conceptual model.</label></li>
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<section id="explain-critical-conceptual-design-decisions" class="level2" data-number="2.2">
<h2 data-number="2.2" class="anchored" data-anchor-id="explain-critical-conceptual-design-decisions"><span class="header-section-number">2.2</span> Explain critical conceptual design decisions</h2>
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<p><em>List and explain critical conceptual design decisions <span class="citation" data-cites="Grimm:2014es">(<a href="#ref-Grimm:2014es" role="doc-biblioref">Grimm et al., 2014</a>)</span>, including:</em></p>
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<li><label><input type="checkbox">spatial and temporal scales,</label></li>
<li><label><input type="checkbox">selection of entities and processes,</label></li>
<li><label><input type="checkbox">representation of stochasticity and heterogeneity,</label></li>
<li><label><input type="checkbox">consideration of local versus global interactions, environmental drivers, etc.</label></li>
<li><label><input type="checkbox">Explain and justify the influence of particular theories, concepts, or earlier models against alternative conceptual design decisions that might lead to alternative model structures.</label></li>
</ul>
</div>
</div>
</section>
<section id="model-assumptions-and-uncertainties" class="level2" data-number="2.3">
<h2 data-number="2.3" class="anchored" data-anchor-id="model-assumptions-and-uncertainties"><span class="header-section-number">2.3</span> Model assumptions and uncertainties</h2>
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<span class="screen-reader-only">Caution</span>Preregistration Item
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<p><em>Specify key assumptions and uncertainties underlying the model design, describing how uncertainty and variation will be represented in the model <span class="citation" data-cites="Moallemi2019">(<a href="#ref-Moallemi2019" role="doc-biblioref">Moallemi et al., 2019</a>)</span>. Sources of uncertainty may include:</em></p>
<ul class="task-list">
<li><label><input type="checkbox">exogenous uncertainties affecting the system,</label></li>
<li><label><input type="checkbox">parametric uncertainty in input data and</label></li>
<li><label><input type="checkbox">structural / conceptual nonparametric uncertainty in the model.</label></li>
</ul>
</div>
</div>
</section>
<section id="identify-predictor-and-response-variables" class="level2" data-number="2.4">
<h2 data-number="2.4" class="anchored" data-anchor-id="identify-predictor-and-response-variables"><span class="header-section-number">2.4</span> Identify predictor and response variables</h2>
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<p>The identification and definition of primary model input variables should be driven by scenario definitions, and by the scope of the model described in the problem formulation phase <span class="citation" data-cites="Mahmoud2009">(<a href="#ref-Mahmoud2009" role="doc-biblioref">Mahmoud et al., 2009</a>)</span>.</p>
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<span class="screen-reader-only">Caution</span>Preregistration Item
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<p><em>Identify and define system system variables and structures, referencing scenario definitions, and the scope of the model as described within problem formulation:</em></p>
<ul class="task-list">
<li><label><input type="checkbox">What variables would support taking this action or making this decision?</label></li>
<li><label><input type="checkbox">What additional variables may interact with this system (things we can’t control, but can hopefully measure)?</label></li>
<li><label><input type="checkbox">What variables have not been measured, but may interact with the system (often occurs in field or observational studies)?</label></li>
<li><label><input type="checkbox">What variables are index or surrogate measures of variables that we cannot or have not measured?</label></li>
<li><label><input type="checkbox">In what ways do we expect these variables to interact (model structures)?</label></li>
<li><label><input type="checkbox">Explain how any key concepts or terms within problem or decision-making contexts, such as regulatory terms, will be operationalised and defined in a biologically meaningful way to answer the research question appropriately?</label></li>
</ul>
</div>
</div>
</section>
<section id="define-prior-knowledge-data-specification-and-evaluation" class="level2" data-number="2.5">
<h2 data-number="2.5" class="anchored" data-anchor-id="define-prior-knowledge-data-specification-and-evaluation"><span class="header-section-number">2.5</span> Define prior knowledge, data specification and evaluation</h2>
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<p>This section specifies the plan for collecting, processing and preparing data available for parameterisation, determining model structure, and for scenario analysis. It also allows the researchers to disclose any prior interaction with the data.</p>
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<section id="collate-available-data-sources-that-could-be-used-to-parameterise-or-structure-the-model" class="level3" data-number="2.5.1">
<h3 data-number="2.5.1" class="anchored" data-anchor-id="collate-available-data-sources-that-could-be-used-to-parameterise-or-structure-the-model"><span class="header-section-number">2.5.1</span> Collate available data sources that could be used to parameterise or structure the model</h3>
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<p><strong>For pre-existing data (delete as appropriate):</strong></p>
<ul class="task-list">
<li><label><input type="checkbox">Document the identity, quantity and provenance of any data that will be used to develop, identify and test the model.</label></li>
<li><label><input type="checkbox">For each dataset, is the data open or publicly available?</label></li>
<li><label><input type="checkbox">How can the data be accessed? Provide a link or contact as appropriate, indicating any restrictions on the use of data.</label></li>
<li><label><input type="checkbox">Date of download, access, or expected timing of future access.</label></li>
<li><label><input type="checkbox">Describe the source of the data - what entity originally collected this data? (National Data Set, Private Organisational Data, Own Lab Collection, Other Lab Collection, External Contractor, Meta-Analysis, Expert Elicitation, Other).</label></li>
<li><label><input type="checkbox">Codebook and meta-data. If a codebook or other meta-data is available, link to it here and / or upload the document(s).</label></li>
<li><label><input type="checkbox">Prior work based on this dataset - Have you published / presented any previous work based on this dataset? Include any publications, conference presentations (papers, posters), or working papers (in-prep, unpublished, preprints) based on this dataset you have worked on.</label></li>
<li><label><input type="checkbox">Unpublished Prior Research Activity - Describe any prior but unpublished research activity using these data. Be specific and transparent.</label></li>
<li><label><input type="checkbox">Prior knowledge of the current dataset - Describe any prior knowledge of or interaction with the dataset before commencing this study. For example, have you read any reports or publications about this data?</label></li>
<li><label><input type="checkbox">Describe how the data is arranged, in terms of replicates and covariates.</label></li>
</ul>
<p><strong>Sampling Plan (for data you will collect, delete as appropriate):</strong></p>
<ul class="task-list">
<li><label><input type="checkbox">Data collection procedures - describe your data collection process, including how sites and transects or any other physical unit were selected and arranged. Describe any inclusion or exclusion rules, and the study timeline.</label></li>
<li><label><input type="checkbox">Sample Size - Describe the sample size of your study.</label></li>
<li><label><input type="checkbox">Sample Size Rationale - Describe how you determined the appropriate sample size for your study. It could include feasibility constraints, such as time, money or personnel.</label></li>
<li><label><input type="checkbox">If sample size cannot be specified, specify a stopping rule - i.e. how will you decide when to terminate your data collection?</label></li>
</ul>
</div>
</div>
</section>
<section id="data-processing-and-preparation" class="level3" data-number="2.5.2">
<h3 data-number="2.5.2" class="anchored" data-anchor-id="data-processing-and-preparation"><span class="header-section-number">2.5.2</span> Data Processing and Preparation</h3>
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<ul class="task-list">
<li><label><input type="checkbox">Describe any data preparation and processing steps, including manipulation of environmental layers (e.g. standardisation and geographic projection) or variable construction (e.g. Principal Component Analysis).</label></li>
</ul>
</div>
</div>
</section>
<section id="sec-exploratory-analyses" class="level3" data-number="2.5.3">
<h3 data-number="2.5.3" class="anchored" data-anchor-id="sec-exploratory-analyses"><span class="header-section-number">2.5.3</span> Describe any data exploration or preliminary data analyses</h3>
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<p>In many modelling cases, it is necessary to perform preliminary analyses to understand the data and check that assumptions and requirements of the chosen modelling procedures are met. Data exploration prior to model fitting or development may include exploratory analyses to check for collinearity, spatial and temporal coverage, quality and resolution, outliers, or the need for transformations <span class="citation" data-cites="Yates2018">(<a href="#ref-Yates2018" role="doc-biblioref">Yates et al., 2018</a>)</span>.</p>
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<span class="screen-reader-only">Warning</span>Caution! Beware questionable research practices and overfitting
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<p>Any modelling and analysis decisions based on data exploration or preliminary investigations increase the risk of questionable research practices and overfitting <span class="citation" data-cites="Gould2026">(<a href="#ref-Gould2026" role="doc-biblioref">Gould et al., 2026</a>)</span>. Such <em>data-dependent</em> analytic decisions <span class="citation" data-cites="Liu2020">(<a href="#ref-Liu2020" role="doc-biblioref">Y. Liu et al., 2020</a>)</span> should ideally be performed using a small, independent subset of the full dataset in order to avoid model overfitting arising from “data leakage” or “model selection bias” <span class="citation" data-cites="Kapoor2023 Campbell2021 Arnqvist2020">(<a href="#ref-Arnqvist2020" role="doc-biblioref">Arnqvist, 2020</a>; <a href="#ref-Campbell2021" role="doc-biblioref">Campbell, 2021</a>; <a href="#ref-Kapoor2023" role="doc-biblioref">Kapoor & Narayanan, 2023</a>)</span>.</p>
<p>The preregistration item below follows a protocol for registering ‘flexible’ analyses, please see our <a href="https://egouldo.github.io/EcoConsPreReg/adaptive_preregistration_background.html">‘Primer on Adaptive Preregistration’</a> in Gould et al. <span class="citation" data-cites="Gould2024a">(<a href="#ref-Gould2024a" role="doc-biblioref">2024</a>)</span> for details.</p>
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<p><em>For each separate preliminary or investigatory analysis:</em></p>
<ul class="task-list">
<li><label><input type="checkbox">State what quantity or estimand needs to be known in order to proceed with further decision-making about the modelling procedure, stating why the analysis is necessary.</label></li>
<li><label><input type="checkbox">Explain how you will implement this analysis, as well as any techniques you will use to summarise and explore your data.</label></li>
<li><label><input type="checkbox">What method will you use to represent this analysis (graphical, tabular, or otherwise, describe)?</label></li>
<li><label><input type="checkbox">Specify exactly which parts of the data will be used, ensuring that any data subsets used are described in <a href="#sec-calibration-data" class="quarto-xref">Section 4.1.1</a>.</label></li>
<li><label><input type="checkbox">Describe how the results will be interpreted, listing each potential analytic decision, as well as the analysis finding that will trigger each decision, where possible.</label></li>
</ul>
</div>
</div>
</section>
<section id="data-evaluation-exclusion-and-missing-data" class="level3" data-number="2.5.4">
<h3 data-number="2.5.4" class="anchored" data-anchor-id="data-evaluation-exclusion-and-missing-data"><span class="header-section-number">2.5.4</span> Data evaluation, exclusion and missing data</h3>
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<p>Documenting issues with reliability is important because data quality and ecological relevance might be constrained by measurement error, inappropriate experimental design, and heterogeneity and variability inherent in ecological systems <span class="citation" data-cites="Grimm:2014es">(<a href="#ref-Grimm:2014es" role="doc-biblioref">Grimm et al., 2014</a>)</span>. Ideally, model input data should be internally consistent across temporal and spatial scales and resolutions, and appropriate to the problem at hand <span class="citation" data-cites="Mahmoud2009">(<a href="#ref-Mahmoud2009" role="doc-biblioref">Mahmoud et al., 2009</a>)</span>.</p>
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<span class="screen-reader-only">Caution</span>Preregistration Item
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<ul class="task-list">
<li><label><input type="checkbox">Describe how you will determine how reliable the data is for the given model purpose. Ideally, model input data should be internally consistent across temporal and spatial scales and resolutions, and appropriate to the problem at hand</label></li>
<li><label><input type="checkbox">Document any issues with data reliability.</label></li>
<li><label><input type="checkbox">How will you determine what data, if any, will be excluded from your analyses?</label></li>
<li><label><input type="checkbox">How will outliers be handled? Describe rules for identifying outlier data, and for excluding a site, transect, quadrat, year or season, species, trait, etc.</label></li>
<li><label><input type="checkbox">How will you identify and deal with incomplete or missing data?</label></li>
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</section>
</section>
<section id="conceptual-model-evaluation" class="level2" data-number="2.6">
<h2 data-number="2.6" class="anchored" data-anchor-id="conceptual-model-evaluation"><span class="header-section-number">2.6</span> Conceptual model evaluation</h2>
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<ul class="task-list">
<li><label><input type="checkbox">Describe how your conceptual model will be critically evaluated. Evaluation includes both the completeness and suitability of the overall model structure.</label></li>
<li><label><input type="checkbox">How will you critically assess any simplifying assumptions <span class="citation" data-cites="Augusiak:2014gz">(<a href="#ref-Augusiak:2014gz" role="doc-biblioref">Augusiak et al., 2014</a>)</span>?</label></li>
<li><label><input type="checkbox">Will this process will include consultation or feedback from a client, manager, or model user.</label></li>
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</section>
</section>
<section id="formalise-and-specify-model" class="level1" data-number="3">
<h1 data-number="3"><span class="header-section-number">3</span> Formalise and Specify Model</h1>
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<p>In this section describe what quantitative methods you will use to build the model/s, explain how they are relevant to the client/manager/user’s purpose.</p>
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<section id="model-class-modelling-framework-and-approach" class="level2" data-number="3.1">
<h2 data-number="3.1" class="anchored" data-anchor-id="model-class-modelling-framework-and-approach"><span class="header-section-number">3.1</span> Model class, modelling framework and approach</h2>
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<p>Modelling approaches can be described as occurring on a spectrum from correlative or phenomenological to mechanistic or process-based <span class="citation" data-cites="Yates2018">(<a href="#ref-Yates2018" role="doc-biblioref">Yates et al., 2018</a>)</span>; where correlative models use mathematical functions fitted to data to describe underlying processes, and mechanistic models explicitly represent processes and details of component parts of a biological system that are expected to give rise to the data <span class="citation" data-cites="White2019a">(<a href="#ref-White2019a" role="doc-biblioref">White & Marshall, 2019</a>)</span>. A model ‘class,’ ‘family’’ or ‘type’ is often used to describe a set of models each of which has a distinct but related sampling distribution <span class="citation" data-cites="Liu2008">(<a href="#ref-Liu2008" role="doc-biblioref">C. C. Liu & Aitkin, 2008</a>)</span>. The model family is driven by choices about the types of variables covered and the nature of their treatment, as well as structural features of the model, such as link functions, spatial and temporal scales of processes and their interactions <span class="citation" data-cites="Jakeman:2006ii">(<a href="#ref-Jakeman:2006ii" role="doc-biblioref">Jakeman et al., 2006</a>)</span>.</p>
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<span class="screen-reader-only">Caution</span>Preregistration Item
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<li><label><input type="checkbox">Describe what modelling framework, approach or class of model you will use to implement your model and relate your choice to the model purpose and analytical objectives described in <a href="#sec-model-purpose-context-and-problem-context" class="quarto-xref">Section 1.1.2</a> and <a href="#sec-analytical-objectives" class="quarto-xref">Section 1.1.3</a>.</label></li>
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</section>
<section id="choose-model-features-and-family" class="level2" data-number="3.2">
<h2 data-number="3.2" class="anchored" data-anchor-id="choose-model-features-and-family"><span class="header-section-number">3.2</span> Choose model features and family</h2>
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