🤷 stuff... i guess

docs/_tex/index.tex

@@ -456,7 +456,7 @@ \section{Understanding the drivers of species
 environment imposes on a species\ldots{} Maybe we can also think of it
 more in terms of metabolic rate?
 
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+\begin{tcolorbox}[enhanced jigsaw, rightrule=.15mm, colframe=quarto-callout-note-color-frame, opacityback=0, opacitybacktitle=0.6, colbacktitle=quarto-callout-note-color!10!white, coltitle=black, bottomrule=.15mm, titlerule=0mm, arc=.35mm, bottomtitle=1mm, toptitle=1mm, title=\textcolor{quarto-callout-note-color}{\faInfo}\hspace{0.5em}{Box 1 -The anatomy of a food web}, breakable, toprule=.15mm, colback=white, left=2mm, leftrule=.75mm]
 
 \begin{quote}
 Important goal of this box is to highlight the different terminology

docs/_tex/references.bib

@@ -1230,6 +1230,23 @@ @book{mccuneAnalysisEcologicalCommunities2002
   isbn = {0-9721290-0-6}
 }
 
+@article{miloNetworkMotifsSimple2002,
+  title = {Network {{Motifs}}: {{Simple Building Blocks}} of {{Complex Networks}}},
+  shorttitle = {Network {{Motifs}}},
+  author = {Milo, R. and {Shen-Orr}, S. and Itzkovitz, S. and Kashtan, N. and Chklovskii, D. and Alon, U.},
+  year = {2002},
+  month = oct,
+  journal = {Science},
+  volume = {298},
+  number = {5594},
+  pages = {824--827},
+  publisher = {American Association for the Advancement of Science},
+  doi = {10.1126/science.298.5594.824},
+  urldate = {2024-07-05},
+  abstract = {Complex networks are studied across many fields of science. To uncover their structural design principles, we defined ``network motifs,'' patterns of interconnections occurring in complex networks at numbers that are significantly higher than those in randomized networks. We found such motifs in networks from biochemistry, neurobiology, ecology, and engineering. The motifs shared by ecological food webs were distinct from the motifs shared by the genetic networks of Escherichia coli and Saccharomyces cerevisiae or from those found in the World Wide Web. Similar motifs were found in networks that perform information processing, even though they describe elements as different as biomolecules within a cell and synaptic connections between neurons in Caenorhabditis elegans. Motifs may thus define universal classes of networks. This approach may uncover the basic building blocks of most networks.},
+  file = {/Users/tanyastrydom/Zotero/storage/YNC2AV7L/Milo et al. - 2002 - Network Motifs Simple Building Blocks of Complex .pdf}
+}
+
 @article{morales-castillaInferringBioticInteractions2015,
   ids = {mora15ibi},
   title = {Inferring Biotic Interactions from Proxies},

docs/index.html

@@ -189,6 +189,7 @@
 <meta name="citation_reference" content="citation_title=TETRA-EU 1.0: A species-level trophic metaweb of European tetrapods;,citation_abstract=Motivation Documenting potential interactions between species represents a major step towards understanding and predicting the spatial and temporal structure of multi-trophic communities and their functioning. The metaweb concept summarizes the potential trophic (and non-trophic) interactions in a given species pool. As such, it generalizes the regional species pool of community ecology by incorporating the potential relationships between species from different trophic levels along with their functional characteristics. However, although this concept is very attractive theoretically, it has rarely been used to understand the structure of an ecological network, mostly because of data availability. Here, we provide a continental-scale, species-level metaweb for all tetrapods (mammals, breeding birds, reptiles and amphibians) occurring in Europe and in the Northern Mediterranean basin. This metaweb is based on data extracted from the scientific literature, including published papers, books and grey literature. Main type of variable contained For each species considered, we built the network of potential two-way trophic interactions. Spatial location and grain We considered all species occurring in the entire European subcontinent, from Macaronesia (including only the islands belonging politically to Spain and Portugal) to the Ural Mountains (west to east) and from Fennoscandia and U.K. islands to the Mediterranean (north to south). We included Turkey, geographically part of Asia, to provide a complete picture of the north-eastern Mediterranean coast. Time period The data represent information published and/or collected during the last 50 years. Major taxa studied and level of measurement We focused our metaweb on terrestrial tetrapods occurring in the study area. Only species introduced in historical times and currently naturalized were considered; new introductions were excluded. In total, we included 288 mammals, 509 regularly breeding birds, 250 reptiles and 104 amphibians. Software format Data are supplied as semicolon-separated text files.;,citation_author=Luigi Maiorano;,citation_author=Alessandro Montemaggiori;,citation_author=Gentile Francesco Ficetola;,citation_author=Louise O’Connor;,citation_author=Wilfried Thuiller;,citation_publication_date=2020-09;,citation_cover_date=2020-09;,citation_year=2020;,citation_issue=9;,citation_doi=10.1111/geb.13138;,citation_issn=1466-8238;,citation_volume=29;,citation_language=en-US;,citation_journal_title=Global Ecology and Biogeography;">
 <meta name="citation_reference" content="citation_title=Comparison of the predicted and observed secondary structure of T4 phage lysozyme;,citation_abstract=Predictions of the secondary structure of T4 phage lysozyme, made by a number of investigators on the basis of the amino acid sequence, are compared with the structure of the protein determined experimentally by X-ray crystallography. Within the amino terminal half of the molecule the locations of helices predicted by a number of methods agree moderately well with the observed structure, however within the carboxyl half of the molecule the overall agreement is poor. For eleven different helix predictions, the coefficients giving the correlation between prediction and observation range from 0.14 to 0.42. The accuracy of the predictions for both \beta-sheet regions and for turns are generally lower than for the helices, and in a number of instances the agreement between prediction and observation is no better than would be expected for a random selection of residues. The structural predictions for T4 phage lysozyme are much less successful than was the case for adenylate kinase (Schulz et al. (1974) Nature 250, 140–142). No one method of prediction is clearly superior to all others, and although empirical predictions based on larger numbers of known protein structure tend to be more accurate than those based on a limited sample, the improvement in accuracy is not dramatic, suggesting that the accuracy of current empirical predictive methods will not be substantially increased simply by the inclusion of more data from additional protein structure determinations.;,citation_author=B. W. Matthews;,citation_publication_date=1975-10;,citation_cover_date=1975-10;,citation_year=1975;,citation_issue=2;,citation_doi=10.1016/0005-2795(75)90109-9;,citation_issn=0005-2795;,citation_volume=405;,citation_journal_title=Biochimica et Biophysica Acta (BBA) - Protein Structure;">
 <meta name="citation_reference" content="citation_title=Analysis of Ecological Communities;,citation_author=Bruce McCune;,citation_author=James Grace;,citation_publication_date=2002;,citation_cover_date=2002;,citation_year=2002;,citation_isbn=0-9721290-0-6;">
+<meta name="citation_reference" content="citation_title=Network Motifs: Simple Building Blocks of Complex Networks;,citation_abstract=Complex networks are studied across many fields of science. To uncover their structural design principles, we defined “network motifs,” patterns of interconnections occurring in complex networks at numbers that are significantly higher than those in randomized networks. We found such motifs in networks from biochemistry, neurobiology, ecology, and engineering. The motifs shared by ecological food webs were distinct from the motifs shared by the genetic networks of Escherichia coli and Saccharomyces cerevisiae or from those found in the World Wide Web. Similar motifs were found in networks that perform information processing, even though they describe elements as different as biomolecules within a cell and synaptic connections between neurons in Caenorhabditis elegans. Motifs may thus define universal classes of networks. This approach may uncover the basic building blocks of most networks.;,citation_author=R. Milo;,citation_author=S. Shen-Orr;,citation_author=S. Itzkovitz;,citation_author=N. Kashtan;,citation_author=D. Chklovskii;,citation_author=U. Alon;,citation_publication_date=2002-10;,citation_cover_date=2002-10;,citation_year=2002;,citation_issue=5594;,citation_doi=10.1126/science.298.5594.824;,citation_volume=298;,citation_journal_title=Science;,citation_publisher=American Association for the Advancement of Science;">
 <meta name="citation_reference" content="citation_title=Inferring biotic interactions from proxies;,citation_abstract=Inferring biotic interactions from functional, phylogenetic and geographical proxies remains one great challenge in ecology. We propose a conceptual framework to infer the backbone of biotic interaction networks within regional species pools. First, interacting groups are identified to order links and remove forbidden interactions between species. Second, additional links are removed by examination of the geographical context in which species co-occur. Third, hypotheses are proposed to establish interaction probabilities between species. We illustrate the framework using published food-webs in terrestrial and marine systems. We conclude that preliminary descriptions of the web of life can be made by careful integration of data with theory.;,citation_author=Ignacio Morales-Castilla;,citation_author=Miguel G. Matias;,citation_author=Dominique Gravel;,citation_author=Miguel B. Araújo;,citation_publication_date=2015-06;,citation_cover_date=2015-06;,citation_year=2015;,citation_issue=6;,citation_doi=10.1016/j.tree.2015.03.014;,citation_volume=30;,citation_journal_title=Trends in Ecology &amp;amp;amp; Evolution;">
 <meta name="citation_reference" content="citation_title=Networks. An introduction;,citation_author=Mark E. J. Newman;,citation_publication_date=2010;,citation_cover_date=2010;,citation_year=2010;">
 <meta name="citation_reference" content="citation_title=Natural - synthetic - artificial!;,citation_abstract=The terms “natural, “synthetic” and “artificial” are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life.;,citation_author=Peter E. Nielsen;,citation_publication_date=2010-07;,citation_cover_date=2010-07;,citation_year=2010;,citation_issue=1;,citation_doi=10.4161/adna.1.1.12934;,citation_issn=1949-095X;,citation_pmid=21687528;,citation_volume=1;,citation_journal_title=Artificial DNA: PNA &amp;amp;amp; XNA;,citation_publisher=Taylor &amp;amp; Francis;">
@@ -1282,7 +1283,7 @@ <h1 class="unnumbered">References</h1>
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docs/notebooks/model_qualitative-preview.html

@@ -1688,7 +1688,7 @@ <h2 class="anchored" data-anchor-id="visualisation">Visualisation</h2>
 <div id="fig-dendro" class="quarto-figure quarto-figure-center quarto-float anchored">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-dendro-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="../images/dendo.png" class="lightbox" data-gallery="quarto-lightbox-gallery-1" data-glightbox="description: .lightbox-desc-1"><img src="../images/dendo.png" class="img-fluid figure-img"></a>
+<a href="../images/dendo.png" class="lightbox" data-glightbox="description: .lightbox-desc-1" data-gallery="quarto-lightbox-gallery-1"><img src="../images/dendo.png" class="img-fluid figure-img"></a>
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 Dendrogram of the trait table using a hierarchical clustering model, This is based off of the traits table in SuppMat 2)
@@ -2092,7 +2092,7 @@ <h2 class="unnumbered anchored" data-anchor-id="references">References</h2>
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docs/notebooks/model_quantitative-preview.html

@@ -5,7 +5,7 @@
 
     <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
 
-    <meta name="dcterms.date" content="2024-05-15">
+    <meta name="dcterms.date" content="2024-07-05">
 
     <title>SuppMat 3: Benchmarking the different model families</title>
     <style>
@@ -219,7 +219,7 @@ <h1 class="title">SuppMat 3: Benchmarking the different model families</h1>
                 <div>
             <div class="quarto-title-meta-heading">Published</div>
             <div class="quarto-title-meta-contents">
-              <p class="date">May 15, 2024</p>
+              <p class="date">July 5, 2024</p>
             </div>
           </div>
 
@@ -472,7 +472,7 @@ <h2 class="anchored" data-anchor-id="model-benchmarking">Model benchmarking</h2>
 <li>A small (&lt; 1) number will thus be indicative of a ‘bottom-heavy’ network and the opposite for larger numbers</li>
 </ul></li>
 <li><p><strong>Structure:</strong> to determine if we are capturing some higher level of ‘structure’ we are using SVD entropy <span class="citation" data-cites="strydomSVDEntropyReveals2021">(<a href="#ref-strydomSVDEntropyReveals2021" role="doc-biblioref">Strydom, Dalla Riva, and Poisot 2021</a>)</span></p></li>
-<li><p><em>Motifs:</em> We can estract the motifs identified by <span class="citation" data-cites="stoufferEvidenceExistenceRobust2007">Stouffer et al. (<a href="#ref-stoufferEvidenceExistenceRobust2007" role="doc-biblioref">2007</a>)</span>, namely:</p>
+<li><p><em>Motifs:</em> We can extract the motifs <span class="citation" data-cites="miloNetworkMotifsSimple2002 stoufferEvidenceExistenceRobust2007">(<a href="#ref-miloNetworkMotifsSimple2002" role="doc-biblioref">Milo et al. 2002</a>; <a href="#ref-stoufferEvidenceExistenceRobust2007" role="doc-biblioref">Stouffer et al. 2007</a>)</span>, namely:</p>
 <ul>
 <li><p>S1: Number of linear chains</p></li>
 <li><p>S2: Number of omnivory motifs</p></li>
@@ -532,6 +532,9 @@ <h2 class="unnumbered anchored" data-anchor-id="references">References</h2>
 <div id="ref-fortunaHabitatLossStructure2006" class="csl-entry" role="listitem">
 Fortuna, Miguel A., and Jordi Bascompte. 2006. <span>“Habitat Loss and the Structure of Plant-Animal Mutualistic Networks: <span>Mutualistic</span> Networks and Habitat Loss.”</span> <em>Ecology Letters</em> 9 (3): 281–86. <a href="https://doi.org/10.1111/j.1461-0248.2005.00868.x">https://doi.org/10.1111/j.1461-0248.2005.00868.x</a>.
 </div>
+<div id="ref-miloNetworkMotifsSimple2002" class="csl-entry" role="listitem">
+Milo, R., S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii, and U. Alon. 2002. <span>“Network <span>Motifs</span>: <span>Simple Building Blocks</span> of <span>Complex Networks</span>.”</span> <em>Science</em> 298 (5594): 824–27. <a href="https://doi.org/10.1126/science.298.5594.824">https://doi.org/10.1126/science.298.5594.824</a>.
+</div>
 <div id="ref-petcheySizeForagingFood2008" class="csl-entry" role="listitem">
 Petchey, Owen L., Andrew P. Beckerman, Jens O. Riede, and Philip H. Warren. 2008. <span>“Size, Foraging, and Food Web Structure.”</span> <em>Proceedings of the National Academy of Sciences</em> 105 (11): 4191–96. <a href="https://doi.org/10.1073/pnas.0710672105">https://doi.org/10.1073/pnas.0710672105</a>.
 </div>
@@ -949,7 +952,7 @@ <h2 class="unnumbered anchored" data-anchor-id="references">References</h2>
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