From 1c34fb340fe88aa07c3e70cd2836c88e4ef30d52 Mon Sep 17 00:00:00 2001 From: Quarto GHA Workflow Runner Date: Mon, 30 Sep 2024 13:05:52 +0000 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- _tex/index.tex | 178 ++++++---------------- index.docx | Bin 7940990 -> 7939847 bytes index.html | 116 +++----------- index.pdf | Bin 6722698 -> 6719434 bytes notebooks/model_qualitative-preview.html | 2 +- notebooks/model_qualitative.embed.ipynb | 10 +- notebooks/model_qualitative.out.ipynb | 10 +- notebooks/model_quantitative-preview.html | 2 +- notebooks/model_quantitative.embed.ipynb | 6 +- notebooks/model_quantitative.out.ipynb | 6 +- 11 files changed, 84 insertions(+), 248 deletions(-) diff --git a/.nojekyll b/.nojekyll index 13042c5..0ccc6b0 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -273b9757 \ No newline at end of file +b0383ec9 \ No newline at end of file diff --git a/_tex/index.tex b/_tex/index.tex index c31ae25..71f185f 100644 --- a/_tex/index.tex +++ b/_tex/index.tex @@ -370,8 +370,7 @@ \section{Setting the Scene: The Not So Basics of Nodes and prediction process (Banville et al., 2024). One thus needs to be aware of both the criteria that is used to define nodes and edges, and what processes or mechanisms the aggregation of the two represents, as this -will ultimately determine and delimit the way in which a network can and -should be used. +will determine what the network can be used for. \subsubsection{How do we define a node?}\label{how-do-we-define-a-node} @@ -617,8 +616,8 @@ \section{Network construction is network representation in the context of trying to understand the feeding dynamics of a seasonal community. -\begin{tcolorbox}[enhanced jigsaw, coltitle=black, breakable, bottomtitle=1mm, colback=white, opacitybacktitle=0.6, leftrule=.75mm, left=2mm, opacityback=0, bottomrule=.15mm, colframe=quarto-callout-note-color-frame, colbacktitle=quarto-callout-note-color!10!white, toprule=.15mm, arc=.35mm, 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}, titlerule=0mm, toptitle=1mm, rightrule=.15mm] +\begin{tcolorbox}[enhanced jigsaw, left=2mm, opacitybacktitle=0.6, leftrule=.75mm, breakable, toptitle=1mm, bottomtitle=1mm, bottomrule=.15mm, titlerule=0mm, colframe=quarto-callout-note-color-frame, coltitle=black, colback=white, arc=.35mm, toprule=.15mm, colbacktitle=quarto-callout-note-color!10!white, opacityback=0, 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}, rightrule=.15mm] Although it might seem most prudent to be predicting, constructing, and defining networks that are the closest representation of reality there @@ -814,7 +813,7 @@ \subsection{Further development of models and clear strategies for benchmarking the ability of models to recover structure (Allesina et al., 2008). -\subsubsection{At what scale should we be predicting and using +\subsection{At what scale should we be predicting and using networks?}\label{at-what-scale-should-we-be-predicting-and-using-networks} Look at Hutchinson et al. (2019) @@ -832,16 +831,17 @@ \subsubsection{At what scale should we be predicting and using biggest barriers that is affecting the use of networks in applied settings\ldots{} By define I mean both delimiting the time and geographic scale at which a network is aggregated at (Estay et al., -2023). This is important because it can influence the inferences made, -\emph{e.g.,} the large body of work (landscape theory for food web -architecture) that showcases how different species use the landscape -will influence network dynamics (Rooney et al., 2008). There is also a -bit of an interplay with time and data and the different scales that -they may be integrated at - co-occurrence may span decades and just -because two species have been recorded in the same space does not mean -it was at the same timescale (Brimacombe et al., 2024) - -\subsubsection{Feasible, realised, or +2023). We know that space plays a role - the motility of different +species will influence both the dynamics of networks but also serve to +link smaller `subnetworks'/community (Fortin et al., 2021; Rooney et +al., 2008). And so does time \emph{e.g.,} seasonal rewiring (Brimacombe +et al., 2021). There is also a bit of an interplay with time and data +and the different scales that they may be integrated at - co-occurrence +may span decades and just because two species have been recorded in the +same space does not mean it was at the same timescale (Brimacombe et +al., 2024). + +\subsection{Feasible, realised, or sustainable?}\label{feasible-realised-or-sustainable} When do we determine a link to be `real'\ldots{} In the context of @@ -859,130 +859,26 @@ \subsubsection{Feasible, realised, or 2024) is addressing, but again it is integrating this with the feasible/realised axis. -\subsection{Petchey dilemma}\label{petchey-dilemma} - -\subsection{How should we use different -networks?}\label{how-should-we-use-different-networks} - -What for and how we can use networks is perhaps one of the biggest -`gaps' we have in network ecology (Tim's EBV ms), and there is a serious -need to start drawing clear, ecological links between network form and -function (although see Delmas et al., 2019). That being said one of the -most important things we can do is to be aware of the parameter space -that is possible given a specific definition of a network and operate -within those parameters. See table for an overview. Also tie it back to -scale - specifically the idea that the fact that metawebs operate at -evolutionary scales they are not suitable for `dynamic' processes, -although they do have the potential to think about novel species -entering the network/community\ldots{} - -\begin{longtable}[]{@{} - >{\raggedright\arraybackslash}p{(\linewidth - 8\tabcolsep) * \real{0.0673}} - >{\raggedright\arraybackslash}p{(\linewidth - 8\tabcolsep) * \real{0.1571}} - >{\raggedright\arraybackslash}p{(\linewidth - 8\tabcolsep) * \real{0.1763}} - >{\raggedright\arraybackslash}p{(\linewidth - 8\tabcolsep) * \real{0.3045}} - >{\raggedright\arraybackslash}p{(\linewidth - 8\tabcolsep) * \real{0.2853}}@{}} -\caption{An informative table}\tabularnewline -\toprule\noalign{} -\begin{minipage}[b]{\linewidth}\raggedright -Network -\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright -Captures -\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright -Mechanism(s) -\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright -Uses -\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright -Limits -\end{minipage} \\ -\midrule\noalign{} -\endfirsthead -\toprule\noalign{} -\begin{minipage}[b]{\linewidth}\raggedright -Network -\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright -Captures -\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright -Mechanism(s) -\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright -Uses -\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright -Limits -\end{minipage} \\ -\midrule\noalign{} -\endhead -\bottomrule\noalign{} -\endlastfoot -Global metaweb & `diet niche' of all species, who \emph{can} eat who & -evolutionary capacity & list of all possible interactions - -potential interactions of `invading' species - -potential diet shifts - -time/context invariant interactions & structure non-informative of -process - -lacks time/spatial constraint - -`static' representation of links - -local specificity \\ -Regional metaweb & potential links for a given community in space & -evolutionary capacity, co-occurrence & list of all possible interactions - -potential diet shifts - -time/context invariant interactions & lack of time constraint -(co-occurrence can be aggregated over years) \\ -Realised network & given the community context. who eats who & -abundance, predator choice, non trophic interactions & `on the ground' -approximation of interactions (local specificity) - -structure is informative - -dynamic processes \emph{e.g.,} stability/persistence (if modelling not -the representation itself) & lack of broader context - only realised -interactions but not all possible interactions - -need a lot of information of the community - data cost \\ -Structural network & distribution of feeding links & & simulated -networks (low data cost) - -structure - -dynamic processes (but not species specific, community level only) & -assumptions on structure to determine structure - -lack of species specificity \\ -\end{longtable} - -\section{Concluding remarks}\label{concluding-remarks} +\section{The future value of +networks}\label{the-future-value-of-networks} + +It should be clear that there is a high degree of interrelatedness and +overlap between the way a network is constructed (modelled or predicted) +and the process(es) it captures, these are encoded (embedded) within the +network and ultimately influences how the network can and should be used +(Berlow et al., 2008; Petchey et al., 2011). It is probably both this +nuance as well as a lack of clear boundaries and guidelines as to the +links between network form and function (although see Delmas et al., +2019) that has stifled the `productive use' of networks beyond +inventorying the interactions between species. Here we will attempt to +address this by linking some of the different network `types' to some of +the current global challenges in biodiversity. \begin{quote} -what is the future value of networks? +The Terry \& Lewis (2020) paper looks at some methods but is +specifically looking at a bipartite world\ldots{} \end{quote} -I think a big take home will (hopefully) be how different approaches do -better in different situations and so you as an end user need to take -this into consideration and pick accordingly. I think Petchey et al. -(2011) might have (and share) some thoughts on this. I feel like I need -to look at Berlow et al. (2008) but maybe not exactly in this context -but vaguely adjacent. This is sort of the crux of the argument presented -in Brimacombe et al. (2024) as well. - -Do we expect there to be differences when thinking about unipartite vs -bipartite networks? Is there underlying ecology/theory that would assume -that different mechanisms (and thus models) are relevant in these two -`systems'. - -\begin{itemize} -\tightlist -\item - The Terry \& Lewis (2020) paper looks at some methods but is - specifically looking at a bipartite world\ldots{} -\end{itemize} - \section*{References}\label{references} \addcontentsline{toc}{section}{References} @@ -1043,6 +939,12 @@ \section*{References}\label{references} not evidence of ecological interactions. \emph{Ecology Letters}, \emph{23}(7), 1050--1063. \url{https://doi.org/10.1111/ele.13525} +\bibitem[\citeproctext]{ref-brimacombeInferredSeasonalInteraction2021} +Brimacombe, C., Bodner, K., \& Fortin, M.-J. (2021). Inferred seasonal +interaction rewiring of a freshwater stream fish network. +\emph{Ecography}, \emph{44}(2), 219--230. +\url{https://doi.org/10.1111/ecog.05452} + \bibitem[\citeproctext]{ref-brimacombeApplyingMethodIts2024} Brimacombe, C., Bodner, K., \& Fortin, M.-J. (2024). \emph{Applying a method before its proof-of-concept: {A} cautionary tale using inferred @@ -1164,6 +1066,12 @@ \section*{References}\label{references} {Patterns} and processes in ecological networks over space. \emph{Frontiers in Ecology and Evolution}, \emph{11}. +\bibitem[\citeproctext]{ref-fortinNetworkEcologyDynamic2021} +Fortin, M.-J., Dale, M. R. T., \& Brimacombe, C. (2021). Network ecology +in dynamic landscapes. \emph{Proceedings of the Royal Society B: +Biological Sciences}, \emph{288}(1949), rspb.2020.1889, 20201889. +\url{https://doi.org/10.1098/rspb.2020.1889} + \bibitem[\citeproctext]{ref-frickeCollapseTerrestrialMammal2022} Fricke, E. C., Hsieh, C., Middleton, O., Gorczynski, D., Cappello, C. D., Sanisidro, O., Rowan, J., Svenning, J.-C., \& Beaudrot, L. 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Table of contents

  • 4 Making Progress with Networks
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  • 5 Concluding remarks
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  • 5 The future value of networks
  • References

    • Notebooks

    @@ -430,7 +426,7 @@

    Table of contents

    The provision of this detail ultimately leads to a set of insights and conclusions about whether, when and under what conditions network representations of biodiversity can contribute to the advancement of ecological theory and generate value in predictive ecology. Specifically, we finish this perspective with an overview of fundamental questions in ecology that we think can benefit from network thinking and a proposal that such thinking can accelerate our capacity to predict the impact of multiple stressors on biodiverse communities.

    1 Setting the Scene: The Not So Basics of Nodes and Edges

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    Defining a food web seems simple; it is the representation of the interactions (edges) between species (nodes), however the definition of ‘edges’ and ‘nodes’, as well as the scale at which they are aggregated can take many forms (Poisot, Stouffer, and Kéfi 2016), which ultimately encodes a series of assumptions and criteria within a network. An awareness of variance in the way a food web can be defined is critical as a network (or its adjacency matrix) is both the ‘object’ from which inferences are made (e.g., the interactions between species, or how the structure influences ecosystem level processes) as well as the ‘product’ of either the data collection (Brimacombe et al. 2023) or prediction process (Banville et al. 2024). One thus needs to be aware of both the criteria that is used to define nodes and edges, and what processes or mechanisms the aggregation of the two represents, as this will ultimately determine and delimit the way in which a network can and should be used.

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    Defining a food web seems simple; it is the representation of the interactions (edges) between species (nodes), however the definition of ‘edges’ and ‘nodes’, as well as the scale at which they are aggregated can take many forms (Poisot, Stouffer, and Kéfi 2016), which ultimately encodes a series of assumptions and criteria within a network. An awareness of variance in the way a food web can be defined is critical as a network (or its adjacency matrix) is both the ‘object’ from which inferences are made (e.g., the interactions between species, or how the structure influences ecosystem level processes) as well as the ‘product’ of either the data collection (Brimacombe et al. 2023) or prediction process (Banville et al. 2024). One thus needs to be aware of both the criteria that is used to define nodes and edges, and what processes or mechanisms the aggregation of the two represents, as this will determine what the network can be used for.

    1.0.1 How do we define a node?

    Although this may seem an elementary question in the context of food webs — a node should represent a (taxonomic) species, the reality is that nodes can often represent an aggregation of different species - so called ‘trophic species’ (Yodzis 1982; Williams and Martinez 2000) or segregation of species by life stages (Clegg, Ali, and Beckerman 2018). Practical implications of how we are aggregating the nodes is that the resolution may not always be ‘pixel perfect’, which limits the ability to make (taxonomic) species specific inferences e.g., does species \(a\) eat species \(b\), however there is value in having nodes that represent an aggregation of species, as the distribution of the links between them are more meaningful in terms of understanding energy flow and distribution within the system.

    @@ -524,97 +520,23 @@

    4 Making Progress

    4.1 Further development of models and tools

    There has been a suite of models that have been developed to predict trophic links, however we are lacking in tools that are explicitly taking into consideration estimating both the feasibility as well as realisation of links, i.e., both interactions and structure simultaneously (Strydom et al. 2021). This could be addressed either through the development of tools that do both (predict both interactions and structure), or to develop an ensemble modelling approach (Becker et al. 2022). Alternatively the development of tools that will allow for the downsampling of metawebs into realised networks (e.g., Roopnarine 2006), although deciding exactly what is driving differences between local networks and the regional metaweb might not be that simple (Saravia et al. 2022). Probably also something that aligns with trying to predict interaction strength - because that would be the gold standard (e.g., Wells and O’Hara 2013). Probably also worth just plainly stating that feasibility of developing a model that is both broadly generalisable, but also has local specificity is probably not attainable (Stouffer 2019), and more specifically the potential use of models to untangle/identify the different processes that shape interaction networks (Song and Levine 2024), e.g., Curtsdotter et al. (2019) showcase the use of models to disentangle the drivers of community function and Strydom, Dalla Riva, and Poisot (2021) who identified that networks are less complex than they could be, suggesting that there are constraints on network assembly. In addition to the more intentional development of models we also need to consider the validation of these models, there have been developments and discussions for assessing how well a model recovers pairwise interactions (Strydom et al. 2021; Poisot 2023), although the rate of false-negatives that may be present in the testing data still present a challenge (Catchen et al. 2023), and we still lack clear strategies for benchmarking the ability of models to recover structure (Allesina, Alonso, and Pascual 2008).

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    4.1.1 At what scale should we be predicting and using networks?

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    4.2 At what scale should we be predicting and using networks?

    Look at Hutchinson et al. (2019)

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    We lack a clear agenda (and conceptualisation) as to what the appropriate level of aggregation is for a ‘network’. Realistically most empirical networks are more aligned with metawebs as opposed to realised networks as they are often the result of some sort of aggregation of observations across time, this creates a two-fold problem. Firstly, we need to think about how this affects any sort of development of theory that sits closer to the ‘realised network’ side of the spectrum - how often are we trying to ask and answer questions about realised networks using feasible networks? The second is that this lack of ‘direction’ as to how we should define a network is (actually) probably one of the biggest barriers that is affecting the use of networks in applied settings… By define I mean both delimiting the time and geographic scale at which a network is aggregated at (Estay, Fortin, and López 2023). This is important because it can influence the inferences made, e.g., the large body of work (landscape theory for food web architecture) that showcases how different species use the landscape will influence network dynamics (Rooney, McCann, and Moore 2008). There is also a bit of an interplay with time and data and the different scales that they may be integrated at - co-occurrence may span decades and just because two species have been recorded in the same space does not mean it was at the same timescale (Brimacombe, Bodner, and Fortin 2024)

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    We lack a clear agenda (and conceptualisation) as to what the appropriate level of aggregation is for a ‘network’. Realistically most empirical networks are more aligned with metawebs as opposed to realised networks as they are often the result of some sort of aggregation of observations across time, this creates a two-fold problem. Firstly, we need to think about how this affects any sort of development of theory that sits closer to the ‘realised network’ side of the spectrum - how often are we trying to ask and answer questions about realised networks using feasible networks? The second is that this lack of ‘direction’ as to how we should define a network is (actually) probably one of the biggest barriers that is affecting the use of networks in applied settings… By define I mean both delimiting the time and geographic scale at which a network is aggregated at (Estay, Fortin, and López 2023). We know that space plays a role - the motility of different species will influence both the dynamics of networks but also serve to link smaller ‘subnetworks’/community (Rooney, McCann, and Moore 2008; Fortin, Dale, and Brimacombe 2021). And so does time e.g., seasonal rewiring (Brimacombe, Bodner, and Fortin 2021). There is also a bit of an interplay with time and data and the different scales that they may be integrated at - co-occurrence may span decades and just because two species have been recorded in the same space does not mean it was at the same timescale (Brimacombe, Bodner, and Fortin 2024).

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    4.1.2 Feasible, realised, or sustainable?

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    4.3 Feasible, realised, or sustainable?

    When do we determine a link to be ‘real’… In the context of metawebs this is perhaps clearer - if all things were equal (i.e., community context is irrelevant) would the predator be able to consume the prey. However in the realised space there is also the question of the long term ‘energetic feasibility’ of an interaction - just because an interaction is possible in the now is it able to sustain a population in the long term. And what is the scale for that long term - are we thinking at the generational scale? Because ultimately when we are constructing a network we are aggregating not only across space but also across time… This is probably again a Lokta-Volterra space question and something that the dynamic foodweb model (Lajaaiti et al. 2024; Delmas et al. 2017; Curtsdotter et al. 2019) is addressing, but again it is integrating this with the feasible/realised axis.

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    4.2 Petchey dilemma

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    4.3 How should we use different networks?

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    What for and how we can use networks is perhaps one of the biggest ‘gaps’ we have in network ecology (Tim’s EBV ms), and there is a serious need to start drawing clear, ecological links between network form and function (although see Delmas et al. 2019). That being said one of the most important things we can do is to be aware of the parameter space that is possible given a specific definition of a network and operate within those parameters. See table for an overview. Also tie it back to scale - specifically the idea that the fact that metawebs operate at evolutionary scales they are not suitable for ‘dynamic’ processes, although they do have the potential to think about novel species entering the network/community…

    - - ------- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    An informative table
    NetworkCapturesMechanism(s)UsesLimits
    Global metaweb‘diet niche’ of all species, who can eat whoevolutionary capacity

    list of all possible interactions

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    potential interactions of ‘invading’ species

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    potential diet shifts

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    time/context invariant interactions

    structure non-informative of process

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    lacks time/spatial constraint

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    ‘static’ representation of links

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    local specificity

    Regional metawebpotential links for a given community in spaceevolutionary capacity, co-occurrence

    list of all possible interactions

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    potential diet shifts

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    time/context invariant interactions

    		lack of time constraint (co-occurrence can be aggregated over years)
    Realised networkgiven the community context. who eats whoabundance, predator choice, non trophic interactions

    ‘on the ground’ approximation of interactions (local specificity)

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    structure is informative

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    dynamic processes e.g., stability/persistence (if modelling not the representation itself)

    lack of broader context - only realised interactions but not all possible interactions

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    need a lot of information of the community - data cost

    Structural networkdistribution of feeding links

    simulated networks (low data cost)

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    structure

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    dynamic processes (but not species specific, community level only)

    assumptions on structure to determine structure

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    lack of species specificity

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    5 Concluding remarks

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    5 The future value of networks

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    It should be clear that there is a high degree of interrelatedness and overlap between the way a network is constructed (modelled or predicted) and the process(es) it captures, these are encoded (embedded) within the network and ultimately influences how the network can and should be used (Petchey et al. 2011; Berlow, Brose, and Martinez 2008). It is probably both this nuance as well as a lack of clear boundaries and guidelines as to the links between network form and function (although see Delmas et al. 2019) that has stifled the ‘productive use’ of networks beyond inventorying the interactions between species. Here we will attempt to address this by linking some of the different network ‘types’ to some of the current global challenges in biodiversity.

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    what is the future value of networks?

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    The Terry and Lewis (2020) paper looks at some methods but is specifically looking at a bipartite world…

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    I think a big take home will (hopefully) be how different approaches do better in different situations and so you as an end user need to take this into consideration and pick accordingly. I think Petchey et al. (2011) might have (and share) some thoughts on this. I feel like I need to look at Berlow, Brose, and Martinez (2008) but maybe not exactly in this context but vaguely adjacent. This is sort of the crux of the argument presented in Brimacombe, Bodner, and Fortin (2024) as well.

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    Do we expect there to be differences when thinking about unipartite vs bipartite networks? Is there underlying ecology/theory that would assume that different mechanisms (and thus models) are relevant in these two ‘systems’.

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    • The Terry and Lewis (2020) paper looks at some methods but is specifically looking at a bipartite world…
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    References

    @@ -649,6 +571,9 @@

    References

    Brimacombe, Chris, Korryn Bodner, and Marie-Josee Fortin. 2024. “Applying a Method Before Its Proof-of-Concept: A Cautionary Tale Using Inferred Food Webs.” https://doi.org/10.13140/RG.2.2.22076.65927.
    +
    +Brimacombe, Chris, Korryn Bodner, and Marie-Josée Fortin. 2021. “Inferred Seasonal Interaction Rewiring of a Freshwater Stream Fish Network.” Ecography 44 (2): 219–30. https://doi.org/10.1111/ecog.05452. +
    Brimacombe, Chris, Korryn Bodner, Matthew Michalska-Smith, Timothée Poisot, and Marie-Josée Fortin. 2023. “Shortcomings of Reusing Species Interaction Networks Created by Different Sets of Researchers.” PLOS Biology 21 (4): e3002068. https://doi.org/10.1371/journal.pbio.3002068.
    @@ -706,6 +631,9 @@

    References

    Estay, Sergio A., Marie-Josée Fortin, and Daniela N. López. 2023. “Editorial: Patterns and Processes in Ecological Networks over Space.” Frontiers in Ecology and Evolution 11.
    +
    +Fortin, Marie-Josée, Mark R. T. Dale, and Chris Brimacombe. 2021. “Network Ecology in Dynamic Landscapes.” Proceedings of the Royal Society B: Biological Sciences 288 (1949): rspb.2020.1889, 20201889. https://doi.org/10.1098/rspb.2020.1889. +
    Fricke, Evan C., Chia Hsieh, Owen Middleton, Daniel Gorczynski, Caroline D. Cappello, Oscar Sanisidro, John Rowan, Jens-Christian Svenning, and Lydia Beaudrot. 2022. “Collapse of Terrestrial Mammal Food Webs Since the Late Pleistocene.” Science 377 (6609): 1008–11. https://doi.org/10.1126/science.abn4012.
    @@ -1326,7 +1254,7 @@

    References

    }); -