🔨 tinkering tweak

docs/_tex/index.tex

@@ -616,8 +616,8 @@ \section{Network construction is
 representations in the context of trying to understand the feeding
 dynamics of a seasonal community.
 
-\begin{tcolorbox}[enhanced jigsaw, opacitybacktitle=0.6, left=2mm, title=\textcolor{quarto-callout-note-color}{\faInfo}\hspace{0.5em}{Box 1 - Why we need to aggregate networks at different scales: A
-hypothetical case study}, arc=.35mm, colbacktitle=quarto-callout-note-color!10!white, leftrule=.75mm, toprule=.15mm, breakable, toptitle=1mm, opacityback=0, coltitle=black, titlerule=0mm, colback=white, rightrule=.15mm, colframe=quarto-callout-note-color-frame, bottomtitle=1mm, bottomrule=.15mm]
+\begin{tcolorbox}[enhanced jigsaw, toptitle=1mm, bottomtitle=1mm, arc=.35mm, colbacktitle=quarto-callout-note-color!10!white, breakable, titlerule=0mm, bottomrule=.15mm, title=\textcolor{quarto-callout-note-color}{\faInfo}\hspace{0.5em}{Box 1 - Why we need to aggregate networks at different scales: A
+hypothetical case study}, left=2mm, opacitybacktitle=0.6, colframe=quarto-callout-note-color-frame, coltitle=black, opacityback=0, rightrule=.15mm, toprule=.15mm, leftrule=.75mm, colback=white]
 
 Although it might seem most prudent to be predicting, constructing, and
 defining networks that are the closest representation of reality there
@@ -803,18 +803,18 @@ \subsection{At what scale should we be predicting and using
 between different scales (Saravia et al., 2022), as well as to what the
 appropriate level of aggregation is for a `network' (Estay et al.,
 2023). Which presents a challenge both in deciding what the appropriate
-spatial (which influences both network properties (Galiana et al.,
-2018), as well as dynamics (Fortin et al., 2021; Rooney et al., 2008)),
-and time scales (\emph{e.g.,} accounting for seasonal turnover in
-communities (Brimacombe et al., 2021; Laender et al., 2010) and
-different timescales of co-occurrence records (Brimacombe et al., 2024))
-are for constructing not only a network but also which type of network
-representation. Although multilayer networks may allow us to encode the
-nuances of space and time (Hutchinson et al., 2019) we still need to
-understand the implications of \emph{e.g.,} constructing networks that
-are not at ecologically but rather politically relevant scales (Strydom
-et al., 2022) and what we can learn or infer from networks a these
-scales.
+spatial and time scales are for constructing not only a network but also
+which type of network representation. Space influences both network
+properties (Galiana et al., 2018), as well as dynamics (Fortin et al.,
+2021; Rooney et al., 2008), and time has implications when it comes to
+accounting for seasonal turnover in communities (Brimacombe et al.,
+2021; Laender et al., 2010) as well as thinking co-occurrence,
+particularly the records used to determine it (Brimacombe et al., 2024).
+Although multilayer networks may allow us to encode the nuances of space
+and time (Hutchinson et al., 2019) we still need to understand the
+implications of \emph{e.g.,} constructing networks that are not at
+ecologically but rather politically relevant scales (Strydom et al.,
+2022) and what we can learn or infer from networks a these scales.
 
 \section{The future value of
 networks}\label{the-future-value-of-networks}

docs/index.html

@@ -519,7 +519,7 @@ <h2 data-number="4.1" class="anchored" data-anchor-id="further-development-of-mo
 </section>
 <section id="at-what-scale-should-we-be-predicting-and-using-networks" class="level2" data-number="4.2">
 <h2 data-number="4.2" class="anchored" data-anchor-id="at-what-scale-should-we-be-predicting-and-using-networks"><span class="header-section-number">4.2</span> At what scale should we be predicting and using networks?</h2>
-<p>We lack an understanding of which processes drive the differences between different scales <span class="citation" data-cites="saraviaEcologicalNetworkAssembly2022">(<a href="#ref-saraviaEcologicalNetworkAssembly2022" role="doc-biblioref">Saravia et al. 2022</a>)</span>, as well as to what the appropriate level of aggregation is for a ‘network’ <span class="citation" data-cites="estayEditorialPatternsProcesses2023">(<a href="#ref-estayEditorialPatternsProcesses2023" role="doc-biblioref">Estay, Fortin, and López 2023</a>)</span>. Which presents a challenge both in deciding what the appropriate spatial (which influences both network properties <span class="citation" data-cites="galianaSpatialScalingSpecies2018">(<a href="#ref-galianaSpatialScalingSpecies2018" role="doc-biblioref">Galiana et al. 2018</a>)</span>, as well as dynamics <span class="citation" data-cites="rooneyLandscapeTheoryFood2008 fortinNetworkEcologyDynamic2021">(<a href="#ref-rooneyLandscapeTheoryFood2008" role="doc-biblioref">Rooney, McCann, and Moore 2008</a>; <a href="#ref-fortinNetworkEcologyDynamic2021" role="doc-biblioref">Fortin, Dale, and Brimacombe 2021</a>)</span>), and time scales (<em>e.g.,</em> accounting for seasonal turnover in communities <span class="citation" data-cites="brimacombeInferredSeasonalInteraction2021 laenderCarbonTransferHerbivore2010">(<a href="#ref-brimacombeInferredSeasonalInteraction2021" role="doc-biblioref">Brimacombe, Bodner, and Fortin 2021</a>; <a href="#ref-laenderCarbonTransferHerbivore2010" role="doc-biblioref">Laender et al. 2010</a>)</span> and different timescales of co-occurrence records <span class="citation" data-cites="brimacombeApplyingMethodIts2024">(<a href="#ref-brimacombeApplyingMethodIts2024" role="doc-biblioref">Brimacombe, Bodner, and Fortin 2024</a>)</span>) are for constructing not only a network but also which type of network representation. Although multilayer networks may allow us to encode the nuances of space and time <span class="citation" data-cites="hutchinsonSeeingForestTrees2019">(<a href="#ref-hutchinsonSeeingForestTrees2019" role="doc-biblioref">Hutchinson et al. 2019</a>)</span> we still need to understand the implications of <em>e.g.,</em> constructing networks that are not at ecologically but rather politically relevant scales <span class="citation" data-cites="strydomFoodWebReconstruction2022">(<a href="#ref-strydomFoodWebReconstruction2022" role="doc-biblioref">Strydom et al. 2022</a>)</span> and what we can learn or infer from networks a these scales.</p>
+<p>We lack an understanding of which processes drive the differences between different scales <span class="citation" data-cites="saraviaEcologicalNetworkAssembly2022">(<a href="#ref-saraviaEcologicalNetworkAssembly2022" role="doc-biblioref">Saravia et al. 2022</a>)</span>, as well as to what the appropriate level of aggregation is for a ‘network’ <span class="citation" data-cites="estayEditorialPatternsProcesses2023">(<a href="#ref-estayEditorialPatternsProcesses2023" role="doc-biblioref">Estay, Fortin, and López 2023</a>)</span>. Which presents a challenge both in deciding what the appropriate spatial and time scales are for constructing not only a network but also which type of network representation. Space influences both network properties <span class="citation" data-cites="galianaSpatialScalingSpecies2018">(<a href="#ref-galianaSpatialScalingSpecies2018" role="doc-biblioref">Galiana et al. 2018</a>)</span>, as well as dynamics <span class="citation" data-cites="rooneyLandscapeTheoryFood2008 fortinNetworkEcologyDynamic2021">(<a href="#ref-rooneyLandscapeTheoryFood2008" role="doc-biblioref">Rooney, McCann, and Moore 2008</a>; <a href="#ref-fortinNetworkEcologyDynamic2021" role="doc-biblioref">Fortin, Dale, and Brimacombe 2021</a>)</span>, and time has implications when it comes to accounting for seasonal turnover in communities <span class="citation" data-cites="brimacombeInferredSeasonalInteraction2021 laenderCarbonTransferHerbivore2010">(<a href="#ref-brimacombeInferredSeasonalInteraction2021" role="doc-biblioref">Brimacombe, Bodner, and Fortin 2021</a>; <a href="#ref-laenderCarbonTransferHerbivore2010" role="doc-biblioref">Laender et al. 2010</a>)</span> as well as thinking co-occurrence, particularly the records used to determine it <span class="citation" data-cites="brimacombeApplyingMethodIts2024">(<a href="#ref-brimacombeApplyingMethodIts2024" role="doc-biblioref">Brimacombe, Bodner, and Fortin 2024</a>)</span>. Although multilayer networks may allow us to encode the nuances of space and time <span class="citation" data-cites="hutchinsonSeeingForestTrees2019">(<a href="#ref-hutchinsonSeeingForestTrees2019" role="doc-biblioref">Hutchinson et al. 2019</a>)</span> we still need to understand the implications of <em>e.g.,</em> constructing networks that are not at ecologically but rather politically relevant scales <span class="citation" data-cites="strydomFoodWebReconstruction2022">(<a href="#ref-strydomFoodWebReconstruction2022" role="doc-biblioref">Strydom et al. 2022</a>)</span> and what we can learn or infer from networks a these scales.</p>
 </section>
 </section>
 <section id="the-future-value-of-networks" class="level1" data-number="5">
@@ -1285,7 +1285,7 @@ <h1 class="unnumbered">References</h1>
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docs/notebooks/model_qualitative-preview.html

@@ -2092,7 +2092,7 @@ <h2 class="unnumbered anchored" data-anchor-id="references">References</h2>
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 });
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docs/notebooks/model_quantitative-preview.html

@@ -501,7 +501,7 @@ <h2 class="anchored" data-anchor-id="visualising-results">Visualising results</h
 <div id="fig-boxplot" class="quarto-figure quarto-figure-center quarto-float anchored">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-boxplot-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="../images/boxplot.png" class="lightbox" data-glightbox="description: .lightbox-desc-1" data-gallery="quarto-lightbox-gallery-1"><img src="../images/boxplot.png" class="img-fluid figure-img"></a>
+<a href="../images/boxplot.png" class="lightbox" data-gallery="quarto-lightbox-gallery-1" data-glightbox="description: .lightbox-desc-1"><img src="../images/boxplot.png" class="img-fluid figure-img"></a>
 </div>
 <figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig" id="fig-boxplot-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Boxplot
@@ -512,7 +512,7 @@ <h2 class="anchored" data-anchor-id="visualising-results">Visualising results</h
 <div id="fig-topology" class="quarto-figure quarto-figure-center quarto-float anchored">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-topology-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="../images/topology.png" class="lightbox" data-glightbox="description: .lightbox-desc-2" data-gallery="quarto-lightbox-gallery-2"><img src="../images/topology.png" class="img-fluid figure-img"></a>
+<a href="../images/topology.png" class="lightbox" data-gallery="quarto-lightbox-gallery-2" data-glightbox="description: .lightbox-desc-2"><img src="../images/topology.png" class="img-fluid figure-img"></a>
 </div>
 <figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig" id="fig-topology-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Differences
@@ -952,7 +952,7 @@ <h2 class="unnumbered anchored" data-anchor-id="references">References</h2>
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index.qmd

@@ -157,7 +157,7 @@ There has been a suite of models that have been developed to predict feeding lin
 
 ## At what scale should we be predicting and using networks?
 
-We lack an understanding of which processes drive the differences between different scales [@saraviaEcologicalNetworkAssembly2022], as well as to what the appropriate level of aggregation is for a 'network' [@estayEditorialPatternsProcesses2023]. Which presents a challenge both in deciding what the appropriate spatial (which influences both network properties [@galianaSpatialScalingSpecies2018], as well as dynamics [@rooneyLandscapeTheoryFood2008; @fortinNetworkEcologyDynamic2021]), and time scales (*e.g.,* accounting for seasonal turnover in communities [@brimacombeInferredSeasonalInteraction2021; @laenderCarbonTransferHerbivore2010] and different timescales of co-occurrence records [@brimacombeApplyingMethodIts2024]) are for constructing not only a network but also which type of network representation. Although multilayer networks may allow us to encode the nuances of space and time [@hutchinsonSeeingForestTrees2019] we still need to understand the implications of *e.g.,* constructing networks that are not at ecologically but rather politically relevant scales [@strydomFoodWebReconstruction2022] and what we can learn or infer from networks a these scales.
+We lack an understanding of which processes drive the differences between different scales [@saraviaEcologicalNetworkAssembly2022], as well as to what the appropriate level of aggregation is for a 'network' [@estayEditorialPatternsProcesses2023]. Which presents a challenge both in deciding what the appropriate spatial and time scales are for constructing not only a network but also which type of network representation. Space influences both network properties [@galianaSpatialScalingSpecies2018], as well as dynamics [@rooneyLandscapeTheoryFood2008; @fortinNetworkEcologyDynamic2021], and time has implications when it comes to accounting for seasonal turnover in communities [@brimacombeInferredSeasonalInteraction2021; @laenderCarbonTransferHerbivore2010] as well as thinking co-occurrence, particularly the records used to determine it [@brimacombeApplyingMethodIts2024]. Although multilayer networks may allow us to encode the nuances of space and time [@hutchinsonSeeingForestTrees2019] we still need to understand the implications of *e.g.,* constructing networks that are not at ecologically but rather politically relevant scales [@strydomFoodWebReconstruction2022] and what we can learn or infer from networks a these scales.
 
 # The future value of networks