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diff --git a/MarineSDMs.docx b/MarineSDMs.docx
diff --git a/MarineSDMs.pdf b/MarineSDMs.pdf
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 <ul>
 <li><a href="https://biomodhub.github.io/biomod2/"><code>biomod2</code></a><br>
 <em>Species distribution modeling, calibration and evaluation, ensemble modeling<br>
-</em><a href="https://biomodhub.github.io/biomod2/articles/pictures/SCHEMA_BIOMOD2_WORKFLOW_functions.png" class="lightbox" title="Graphical overview of `biomod2` functions for data formatting, single SDMs, ensemble methods and visualization. Source: [`biomod2`](https://biomodhub.github.io/biomod2/)" data-gallery="quarto-lightbox-gallery-1"><img src="https://biomodhub.github.io/biomod2/articles/pictures/SCHEMA_BIOMOD2_WORKFLOW_functions.png" class="img-fluid" alt="Graphical overview of `biomod2` functions for data formatting, single SDMs, ensemble methods and visualization. Source: [`biomod2`](https://biomodhub.github.io/biomod2/)"></a></li>
+</em><a href="https://biomodhub.github.io/biomod2/articles/pictures/SCHEMA_BIOMOD2_WORKFLOW_functions.png" class="lightbox" data-gallery="quarto-lightbox-gallery-1" title="Graphical overview of `biomod2` functions for data formatting, single SDMs, ensemble methods and visualization. Source: [`biomod2`](https://biomodhub.github.io/biomod2/)"><img src="https://biomodhub.github.io/biomod2/articles/pictures/SCHEMA_BIOMOD2_WORKFLOW_functions.png" class="img-fluid" alt="Graphical overview of `biomod2` functions for data formatting, single SDMs, ensemble methods and visualization. Source: [`biomod2`](https://biomodhub.github.io/biomod2/)"></a></li>
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-<p><a href="figures/rocr.png" class="lightbox" title="ROC curve generated by showing rates of false positive vs false negative as function of changing the threshold value (rainbow colors). Source: ROCR: visualizing classifier performance in R" data-gallery="quarto-lightbox-gallery-1"><img src="figures/rocr.png" class="img-fluid figure-img"></a></p>
+<p><a href="figures/rocr.png" class="lightbox" data-gallery="quarto-lightbox-gallery-1" title="ROC curve generated by showing rates of false positive vs false negative as function of changing the threshold value (rainbow colors). Source: ROCR: visualizing classifier performance in R"><img src="figures/rocr.png" class="img-fluid figure-img"></a></p>
 <figcaption class="figure-caption">Figure&nbsp;11.1: ROC curve generated by showing rates of false positive vs false negative as function of changing the threshold value (rainbow colors). Source: <a href="https://cran.rstudio.com/web/packages/ROCR/vignettes/ROCR.html">ROCR: visualizing classifier performance in R</a></figcaption>
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diff --git a/explorations/am-envelope.html b/explorations/am-envelope.html
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