name: title layout: true class: center, middle, style1 --- # THE TITLE IS OBVIOUSLY MISSING
### [Kevin Cazelles](http://kevincazelles.fr), [Universty of Guelph](https://www.uoguelph.ca/) [![:fontawe](github)](https://github.com/KevCaz/seminarInteractionsDistributions)
### Département de biologie, Université de Sherbrooke #### October, 12
th
2018 --- name: style1 layout: true class: style1 --- # ABOUT ME
## Theory - biogeography - co-occurrence - food webs - population dynamics - homogenezation -- ## Statistics, algorithms, data, software .right[
] ### .left[[inSileco: codes, ideas and methods in ecology](https://insileco.github.io/)] --- name: title layout: true class: center, middle, style1 --- # DO BIOTIC INTERACTIONS IMPACT GEOGRAPHIC RANGE LIMITS OF SPECIES?
### [Kevin Cazelles](http://kevincazelles.fr), [Universty of Guelph](https://www.uoguelph.ca/) [![:fontawe](github)](https://github.com/KevCaz/seminarInteractionsDistributions)
### Département de biologie, Université de Sherbrooke #### October, 12
th
2018 --- name: style2 layout: true class: center middle, style2 --- # INTRODUCTION
### Biogeography and biotic interactions --- name: style1 layout: true class: style1 --- # Biogeography: distributions
.center[![:scale 100%](fig/biogeo/ecoreg.png)] --- # Biogeography: distributions
.center[![:scale 100%](fig/biogeo/figmapw3.png)] --- # Biogeography: processes
.center[![:scale 100%](fig/mech/figall1.png)] --- # Individuals
.center[![:scale 100%](fig/mech/figall2.png)] --- # Individuals to population
.center[![:scale 100%](fig/mech/figall3.png)] ??? Interaction at this scale that one can actually envision interactions --- # Population to metapopulation
.center[![:scale 100%](fig/mech/figall4.png)] ??? Interaction at this scale that one can actually envision interactions --- # Populations to metapopulations
.center[![:scale 100%](fig/mech/figall5.png)] ??? Interaction at this scale that one can actually envision interactions --- # Metapopulations to metacommunities
.center[![:scale 100%](fig/mech/figall6.png)] ??? Interaction at this scale that one can actually envision interactions --- # Metacommunities through time
.center[![:scale 100%](fig/mech/figall7.png)] ??? We scaled up in space Let's sclaed up in time Lots of process to take into account ! That explain why species are here... Lot's of processes le'ts recap --- # Metacommunities through time
.center[![:scale 100%](fig/mech/figall8.png)] --- # Metacommunities through time
.center[![:scale 100%](fig/mech/figall9.png)] --- # Biogeography: processes
## 1. Abiotic variables -- ## 2. Dispersion -- ## 3. Ecological interactions -- ## 4. Historical factors --
# .center[[INTERDEPENDENT]()] --- # Biogeography: questions
-- ## How processes generate distributions? ## How to infer processes from distributions? --- # Biogeography: challenge
.center[![:scale 100%](./fig/figdem0.png)] --- # Biogeography: challenge
.center[![:scale 100%](./fig/figdem1.png)] --- # Biogeography: challenge
.center[![:scale 100%](./fig/figdem2.png)] --- # Species Distribution Models (SDMs)
.center[![:scale 100%](./fig/figgrad1.png)] --- # Species Distribution Models (SDMs)
.center[![:scale 100%](./fig/figgrad2.png)] --- # Predicting species distributions
.center[![:scale 100%](./fig/figdem3.png)] --- # Predicting species distributions
.center[![:scale 100%](./fig/figdem4.png)] --- # Species Distribution Models (SDMs)
.center[![:scale 100%](./fig/figgrad3.png)] --- # Species Distribution Models (SDMs)
.center[![:scale 100%](./fig/figgrad4.png)] --- # Predicting species distributions
.center[![:scale 100%](./fig/figdem5.png)] --- # Predicting species distributions
## Species are assumed independent -- ### ![:fontawe](file-text) Davis *et al*, 1998, *Nature* --
## Joint Species Distribution Models (JSDMs) ### ![:fontawe](file-text) Clark *et al*, 2014, *Ecological Applications* ### ![:fontawe](file-text) Pollock *et al*, 2014, *Methods in Ecology and Evolution* ### ![:fontawe](file-text) Zurell *et al*, 2018, *Ecography* --- # Predicting species distributions
-- ## Theory ### ![:fontawe](file-text) Holt, *Toward a Trophic Island Biogeography*, 2009. [![:fontawe](external-link)](https://press.princeton.edu/titles/9096.html) ### ![:fontawe](file-text) Gravel *et al.*, *Ecology Letters*, 2011.[![:fontawe](external-link)]((http://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2011.01667.x/abstract) ### ![:fontawe](file-text) Massol *et al.*, *Advances in Ecological Research*, 2017.[![:fontawe](external-link)]((https://doi.org/10.1016/bs.aecr.2016.10.004) --- # Biogeography: challenge
.center[![:scale 100%](./fig/figdem6.png)] --- # Biogeography: challenge
.center[![:scale 100%](./fig/figdem7.png)] --- # Questions
### How interactions influence species distributions? ### How to infer the role of biotic interactions from co-occurrence data?
-- 1. How to integrate biotic interactions into SDMs? -- 2. How the properties of ecological networks influence co-occurrence? -- 3. Can we infer interactions from co-occurrence data? ??? des why / des hypothèses et des how --- name: style2 layout: true class: center, middle, style2 --- # THEORY OF ISLAND BIOGEOGRAPHY AND BIOTIC INTERACTIONS
### How to integrate biotic interactions into SDMs? --- name: style1 layout: true class: style1 --- # MacArthur et Wilson (1963, 1967)
--- # MacArthur et Wilson (1963, 1967)
.center[![:scale 100%](fig/mcaWil/figMW2.png)] --- # MacArthur et Wilson (1963, 1967)
.center[![:scale 100%](fig/mcaWil/figMW3.png)] --- # MacArthur et Wilson (1963, 1967)
.center[![:scale 100%](fig/mcaWil/figMW4.png)] --- # MacArthur et Wilson (1963, 1967)
.center[![:scale 100%](fig/mcaWil/figMW5.png)] --- # MacArthur et Wilson (1963, 1967)
.center[![:scale 100%](fig/mcaWil/figMW6.png)] --- # MacArthur et Wilson (1963, 1967)
.center[![:scale 100%](fig/mcaWil/figMW7.png)] --- # MacArthur et Wilson (1963, 1967)
.center[![:scale 100%](fig/mcaWil/figMW8.png)] --- # Model properties
### 1. Colonisation/extinction dynamics --
### 2. Equilibrium --
### 3. Elegant, easy to build on it --
### 4. Biotic and abiotic constraints are missing ??? ça marche bien... et très utilisé --- # Releasing the assumption of independence
-- ## Gravel *et al*, 2011, *Ecology Letters* [![:fontawe](external-link)](http://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2011.01667.x/abstract) -- ### 1. Island without prey = no predator colonisation ### 2. Predator without prey = extinction
-- ## Colonisation and extinction depend on the local community
??? première étape pour lever l'hypothèse. --- # What did I do?
.center[![:scale 100%](fig/gtib/figGTIB1.png)] --- # What did I do?
.center[![:scale 100%](fig/gtib/figGTIB2.png)] --- # What did I do?
.center[![:scale 100%](fig/gtib/figGTIB3.png)] --- # What did I do?
.center[![:scale 100%](fig/gtib/figGTIB4.png)] --- # What did I do?
.center[![:scale 100%](fig/gtib/figGTIB5.png)] --- # What did I do?
.center[![:scale 100%](fig/gtib/figGTIB6.png)] --- # What did I do?
.center[![:scale 100%](fig/gtib/figGTIB7.png)] --- # What did I do?
.center[![:scale 100%](fig/gtib/figGTIB8.png)] --- # Results: the classical theory revisited
.center[![:scale 100%](./fig/figgtib0.png)] --- # Results: the classical theory revisited
.center[![:scale 100%](./fig/figgtib1.png)] --- # Results: the classical theory revisited
.center[![:scale 100%](./fig/figgtib2.png)] --- # Results: the classical theory revisited
.center[![:scale 100%](./fig/figgtib3.png)] --- # Results: the classical theory revisited
.center[![:scale 100%](./fig/figgtib4.png)] --- # Conclusion and limits
### For `n` species, a network `W`, a set of abiotic variables `E`, --
### Community `\(C_k = \{0, 1, 0, 0, ..., 1, 0\}\)` -- ## `\(P(C_{k,t+1} | C_{l, t}) = f(W, E)\)` --
### .right[[Cazelles *et al.*, *Ecography* (2016).](http://doi.org/10.1111/ecog.01714)] --- # Conclusion and limits
### Community-based biogeography: more than occurrence and co-occurrence
-- ### `\(n\)` species `\(2^n\)` potential communities
-- ### [What is wrong with co-occurrence data for species embedded in a network?]() --- name: style2 layout: true class: center, middle, style2 --- # CO-OCCURRENCE AND ECOLOGICAL NETWORKS
### How the properties of ecological networks influence co-occurrence? --- name: style1 layout: true class: style1 --- # Co-occurrence and biotic interactions
.center[![:scale 100%](./fig/figcooc1.png)] --- # Co-occurrence and biotic interactions
.center[![:scale 100%](./fig/figcooc2.png)] --- # Co-occurrence and biotic interactions
.center[![:scale 100%](./fig/figcooc3.png)] --- # Co-occurrence and biotic interactions
.center[![:scale 100%](./fig/figcooc4.png)] --- # Co-occurrence and biotic interactions
.center[![:scale 100%](./fig/figcooc5.png)] --- # Co-occurrence and biotic interactions
.center[![:scale 100%](./fig/figcooc6.png)] --- # Checkerboard distribution (Diamond 1975)
.center[![:scale 52%](./fig/figCS1.png)] --- # Checkerboard distribution (Diamond 1975)
.center[![:scale 52%](./fig/figCS2.png)] --- # Checkerboard distribution (Diamond 1975)
.center[![:scale 52%](./fig/figCS3.png)] --- # What did I do?
### Checkerboard distrbution in a network context
-- .column[ ### Observed `vs` Expected
### `\(P(X_i,X_j) - P(X_i)P(X_j)\)` ] .column[ ] --- # What did I do?
.column[ ### Observed `vs` Expected
### `\(P(X_i,X_j) - P(X_i)P(X_j)\)` ] .column[ `\(P(X_i,X_j) - P(X_i)P(X_j)=0\)`
.center[![:scale 32%](./fig/figCS1.png)] ] --- # What did I do?
.column[ ### Observed `vs` Expected
### `\(P(X_i,X_j) - P(X_i)P(X_j)\)` ] .column[ `\(P(X_i,X_j) - P(X_i)P(X_j)<0\)`
.center[![:scale 32%](./fig/figCS2.png)] ] --- # What did I do?
.column[ ### Observed `vs` Expected
### `\(P(X_i,X_j) - P(X_i)P(X_j)\)` ] .column[ `\(P(X_i,X_j) - P(X_i)P(X_j)>0\)`
.center[![:scale 32%](./fig/figCS3.png)] ] --- # What did I do?
.column[ ### Observed `vs` Expected
### `\(P(X_i,X_j) - P(X_i)P(X_j)\)`
### Simulated co-occurrence (trophic interactions) ] .column[
.center[![:scale 42%](fig/gtib/figGTIB8.png)] ] --- # What did I do?
.column[ ### Observed `vs` Expected
### `\(P(X_i,X_j) - P(X_i)P(X_j)\)`
### Simulated co-occurrence (trophic interactions)
### Simulated networks ] .column[
.center[![:scale 38%](./fig/figweb.png)] ] --- # Co-occurrence and shortest path
.center[![:scale 100%](./fig/figsht0.png)] --- # Co-occurrence and shortest path
.center[![:scale 100%](./fig/figsht1.png)] --- # Co-occurrence and shortest path
.center[![:scale 100%](./fig/figsht2.png)] --- # Co-occurrence and shortest path
.center[![:scale 100%](./fig/figsht3.png)] --- # Co-occurrence and degree
.center[![:scale 100%](./fig/figdeg0.png)] --- # Co-occurrence and degree
.center[![:scale 100%](./fig/figdeg1.png)] --- # Co-occurrence and degree
.center[![:scale 100%](./fig/figdeg2.png)] --- # Co-occurrence and degree
.center[![:scale 100%](./fig/figdeg3.png)] --- # Conclusion and limits
## Shortest path
`\( \Longrightarrow \)` detection
-- ## Degree
`\( \Longrightarrow \)` detection
--
### .right[[Cazelles *et al.*, *Theoretical Ecology* (2016).](http://doi.org/10.1007/s12080-015-0281-9)] --- # Correlations?
.center[![:scale 100%](./fig/figNew/argument_pred1.png)] --- # Correlations?
.center[![:scale 100%](./fig/figNew/argument_pred2.png)] --- # Correlations?
.center[![:scale 100%](./fig/figNew/argument_pred3.png)] --- # Correlations?
.center[![:scale 100%](./fig/figNew/argument_pred4.png)] --- # Conclusion and limits
## Shortest path
`\( \Longrightarrow \)` detection
## Degree
`\( \Longrightarrow \)` detection
--
## Abiotic variables? -- ## Empirical data? --- name: style2 layout: true class: center, middle, style2 --- # DEALING WITH REAL DATA SETS
### Can we infer interactions from co-occurrence data? --- name: style1 layout: true class: style1 --- # Abiotic variables
.center[![:scale 90%](./fig/figab1.png)] --- # Abiotic variables
.center[![:scale 90%](./fig/figab2.png)] --- # Integrating abiotic variables (E)
# `\(P(X_{i,E},X_{j,E})\)` `vs` `\(P(X_{i,E})P(X_{j,E})\)` --- # Integrating abiotic variables (E)
.center[![:scale 100%](./fig/figshtenv1.png)] --- # Integrating abiotic variables (E)
.center[![:scale 100%](./fig/figshtenv2.png)] --- # What did I do?
### 4 data sets, **know interactions** --
### `\(P(X_{i,E},X_{j,E})\)` `vs` `\(P(X_{i,E})P(X_{j,E})\)` --
### SDMs to assign presence probabilities given abiotic context --
### Detection
once abiotic variables integrated --- # Kopelke *et al.*, *Ecology* (2017)
.column[ .center[![:scale 87%](./fig/mapsal1.png)] ] .column[ .center[![:scale 25%](./img/cool.png)] ] ??? mettre les noms --- # Kopelke *et al.*, *Ecology* (2017)
.column[ .center[![:scale 87%](./fig/mapsal2.png)] ] .column[ .center[![:scale 25%](./img/cool.png)] ] ??? symphyte / ovipositeur --- # Three trophic levels network
# Willow
Galler
Parasitoids # 52
96
126 species --
# Willow
Galler -- # Galler
Parasitoids --- # Willow
Galler - Shortest path
![:scale 100%](./fig/figSG0.png) --- # Willow
Galler - Shortest path
![:scale 100%](./fig/figSG1.png) --- # Willow
Galler - Shortest path
![:scale 100%](./fig/figSG2.png) --- # Willow
Galler - Shortest path
![:scale 100%](./fig/figSG3.png) --- # Willow
Galler - Shortest path
![:scale 100%](./fig/figSG4.png) --- # Willow
Galler - `\(P(X_{i,E},X_{j,E})\)`
![:scale 100%](./fig/figSG5.png) --- # Galler
Parasitoids - `\(P(X_{i,E},X_{j,E})\)`
![:scale 100%](./fig/figGP5.png) --- # Co-occurrence and shortest path
.center[![:scale 100%](./fig/figsht3.png)] --- # Willow
Galler `vs` Galler
Parasitoids
.center[![:scale 53%](./fig/figSG5.png)] .center[![:scale 53%](./fig/figGP5.png)] --- # Willow
Galler `vs` Galler
Parasitoids
.center[![:scale 53%](./fig/figSG6.png)] .center[![:scale 53%](./fig/figGP6.png)] --- # Willow
Galler `vs` Galler
Parasitoids
.center[![:scale 53%](./fig/figSG7.png)] .center[![:scale 53%](./fig/figGP7.png)] --- # Co-occurrence and degree
.center[![:scale 100%](./fig/figdeg3.png)] --- # Conclusion
## Shortest path
`\( \Longrightarrow \)` detection
-- ## Degree
`\( \Longrightarrow \)` detection
-- ## Using empirical data sets. --
### .right[[Cazelles *et al.*, *in prep* (2018).]()] --- name: style2 layout: true class: center, middle, style2 --- # Concluding remarks and perspectives
### Towards better predictions? --- name: style1 layout: true class: style1 --- # Answers
## 1. How to integrate biotic interactions into distribution models? -- ### `\( \Longrightarrow \)` think at the community-scale -- ### `\( \Longrightarrow \)` build Network Distribution Models (NDMs) --- # Answers
## 2. How the properties of ecological networks influence co-occurrence? -- ### `\( \Longrightarrow \)` shortest path
`\( \Longrightarrow \)` detection
### `\( \Longrightarrow \)` degree
`\( \Longrightarrow \)` detection
-- ### We may not need to consider the whole network --- # Answers
## 3. Can we infer interactions from co-occurrence data? -- ### `\( \Longrightarrow \)` depends on the network properties -- ### `\( \Longrightarrow \)` depends on the spatial scale (literature) ??? variations des interactions --- # Is it correct?
.center[![:scale 90%](./fig/figshtenv2.png)] -- ## .center[INTERDEPENDENCY] --- # Towards mechanistic NDMs?
## Better than JSDMs? (more information) -- ## Network Distribution Models (NDMs) --
## Network `\(W\)`, abiotic variables `\(E\)` --
## How to predict interactions? --- # Towards mechanistic NDMs?
.center[![:scale 100%](./fig/figLast1.png)] --- # Towards mechanistic NDMs?
.center[![:scale 100%](./fig/figLast2.png)] --- # Towards mechanistic NDMs?
.center[![:scale 100%](./fig/figLast3.png)] --- # Towards mechanistic NDMs?
.center[![:scale 100%](./fig/figLast4.png)] --- # Towards mechanistic NDMs?
.center[![:scale 100%](./fig/figLast5.png)] --- # Towards mechanistic NDMs?
### 1. **Building a biogeography of ecological networks**
![:fontawe](file-text) [Galiana, N., *et al.* (2018). The spatial scaling of species interaction networks. *Nature Ecology & Evolution*.](https://www.nature.com/articles/s41559-018-0517-3)
-- ### 2. **[Building an energetic framework](https://kevcaz.github.io/talkBES2017/#1)** --- name: style2 layout: true class: center, middle, style2 --- # THANK YOU
### Merci --- name: style2 layout: true class: class: center, middle, style2 --- ## What am I doing these days?
### Science, what else? --- name: style1 layout: true --- # Homogenization
![](img/homogen.png) --- # Rewiring + seasonality in food webs
### [Nature rewires in a changing world](https://peerj.com/preprints/27187/) *Nature Eco Evo* --- # Iscoscape: the push for provenance
### [Fighting noise with dimensionality](https://kevcaz.github.io/fightingNoise/#1) --- name: style2 layout: true class: center, middle, style2 --- # THANK YOU
### Merci --- name: style1 layout: true class: center, style1 --- --- # Urgently needed
## Interactions ++
predictions easier ### Berlow *et al*, 2009, *PNAS* --
## WWF, Living Planet Report 2016 [
](http://awsassets.wwf.ca/downloads/wwf_living_planet_report_2016___risk_and_resilience_in_a_new_era.pdf) > If current trends continue to 2020 > vertebrate populations may decline by an > average of 67 per cent compared to 1970. --- # Using species as predictors?
.center[![:scale 100%](./fig/figAUC1.png)] --- # Using species as predictors?
.center[![:scale 100%](./fig/figAUC2.png)] --- # Using species as predictors?
.center[![:scale 100%](./fig/figAUC3.png)] --- # Using species as predictors?
.center[![:scale 100%](./fig/figAUC4.png)] --- # Using species as predictors?
.center[![:scale 100%](./fig/figAUC5.png)] --- # Using species as predictors?
.center[![:scale 100%](./fig/figAUC6.png)] --- # Using species as predictors?
.center[![:scale 100%](./fig/figAUC7.png)] --- ## Figure 1
![:scale 64%](./figsup/figintro1.png) --- ## Figure 2
![:scale 100%](./figsup/figintro2.png) --- ## Figure 3
![:scale 100%](./figsup/figch11.png) --- ## Figure 4
![:scale 68%](./figsup/figch12.png) --- ## Figure 5
![:scale 68%](./figsup/figch13.png) --- ## Figure 6
![:scale 100%](./figsup/figch14.png) --- ## Figure 7
![:scale 100%](./figsup/figch15.png) --- ## Figure 8
![:scale 100%](./figsup/figch21.png) --- ## Figure 9
![:scale 80%](./figsup/figch31.png) --- ## Figure 10
![:scale 100%](./figsup/figch32.png) --- ## Figure 11 ![:scale 67%](./figsup/figch33.png) --- ## Figure 12 ![:scale 50%](./figsup/figch34.png) --- ## Figure 13
![:scale 40%](./figsup/figch35.png) --- ## Figure 14 ![:scale 32%](./figsup/figch36.png) --- ## Figure 15
.column[![:scale 74%](./figsup/figch37a.png)] .column[![:scale 74%](./figsup/figch37b.png)] --- ## Figure 16
![:scale 70%](./figsup/figch38.png) --- ## Figure 17
![:scale 100%](./figsup/figch39.png) --- ## Figure 18 ![:scale 80%](./figsup/figch310.png) --- ## Figure 19 ![:scale 70%](./figsup/figch311.png) --- ## Figure 21 ![:scale 64%](./figsup/figch312.png) --- ## Figure 21
![:scale 48%](./figsup/figch313.png) --- ## Figure 22
.column[ ![:scale 60%](./figsup/figch41a.png) ] .column[ ![:scale 32%](./figsup/figch41b.png) ![:scale 32%](./figsup/figch41c.png) ] --- ## Figure 23
![:scale 70%](./figsup/figch42.png) --- ## Figure 24
![:scale 73%](./figsup/figch43.png) --- ## Figure 25 ![:scale 64%](./figsup/figch44.png) --- name: style1 layout: true class: style1 --- # Phylopic
- Silhouette image found on [Phylopic](http://phylopic.org/about/) - Silouhette [Ichneumonidae](http://phylopic.org/name/07b2fc56-3489-4007-904b-1a0904ea2647) ; credit Melissa Broussard. --- count:false # Salix data set
### Species on slides 120-121: 1- Female of *Euura lapponica* ovipositing on *Salix lapponum* ; 2- leaf midrib pea gall induced by *Pontania norvegica* on *Salix borealis* ; 3- Larva of *Pontania pustulator* insid1 e opened leaf midrib bean gall on *Salix phylicifolia* ;
> 641 site-visits over 29 years, and on 165,424 galls representing 96 herbivore > nodes and 52 plant nodes. The dissections and rearings yielded 42,129 natural > enemies belonging to 126 species --- name: style1 layout: true class: style1 --- count:false # Null models
-- ### Since 1970 (following Diamond's paper) ### Connor et al., 2013, Ecology.
-- ### Pattern-generating models based on randomization of ecological data ### Some elements are fixed, others vary randomly. --- count:false # Null models
### What would be expected in the absence of a given mechanism?
### Detection of pattern in binary presence–absence matrices. --- count: false # Ulrich & Gotelli, 2013, *Oikos*
## Test 15 indices.
.center[![:scale 74%](./figsup/co-occu.png)] --- count: false # Null models
> Null models of species associations should, thus, be used only to reveal the structure of co-occurrence data. ## Difficult to assign to a particular process --- count:false # MacArthur and Wilson Limits
## Releasing the assumption of a constant pool of species is a KEY -- ## Very challenging though: ### - very large pool of species ### - abondances (metapopulations) ### - evolutionnary process
-- ## All solutions increase the complexity. # ABOUT ME
## PhD (2012-2016) .center[![:scale 80%](img/logo/logos.png)] ### Dominique Gravel / Nicolas Mouquet --
## Post-doc (2017) ### Kevin S. McCann --- # A truism?
### 1- Solar radiation ![:fontawe](long-arrow-right) Autotrophs ![:fontawe](long-arrow-right) Hetreotrophs
-- ### 2- Carbon source
-- ### 3- Water availibility
-- ### 4- Nutrients availibility --- # A truism?
.center[![:scale 100%](fig/biogeo/ecoreg.png)] --- # Model principle
.center[![:scale 100%](fig/gtib/figGTIB9.png)] --- # Model principle
-- ## 1- Cost of a community
-- ## 2- Extinctions ### - Random ###- Energy based --- # Energy cost of a network on an island
.center[![:scale 35%](fig/netenerg1.png)] ### Niche model + body size to derive maintenance metabolism --- # Energy cost of a network on an island
.center[![:scale 45%](fig/netenerg2.png)] --- # Energy cost of a network on an island
.center[![:scale 45%](fig/netenerg3.png)] --- # Energy cost of a network on an island
.center[![:scale 45%](fig/netenerg4.png)] --- # Energy cost of a network on an island
.center[![:scale 45%](fig/netenerg5.png)] --- # Energy cost of a network on an island
.center[![:scale 45%](fig/netenerg6.png)] --- # Cost of a community on an island
.center[![:scale 75%](fig/motifcost1.png)] --- # Cost of a community on an island
.center[![:scale 75%](fig/motifcost2.png)] --- # Cost of a community on an island
.center[![:scale 75%](fig/motifcost3.png)] --- # Model
.center[![:scale 100%](fig/gtib/figGTIB9.png)] --- # SARs become SERs .small[[Wright, *Oikos*, 1983.](https://www.jstor.org/stable/3544109)]
.center[![:scale 100%](fig/figRes11.png)] --- # SARs become SERs
.center[![:scale 100%](fig/figRes12.png)] --- # SARs become SERs
.center[![:scale 100%](fig/figRes13.png)] --- # SARs become SERs
.center[![:scale 100%](fig/figRes14.png)] --- # SARs become SERs
.center[![:scale 100%](fig/figRes15.png)] --- # Mean degree
.center[![:scale 100%](fig/figRes21.png)] --- # Mean degree
.center[![:scale 100%](fig/figRes22.png)] --- # Mean degree
.center[![:scale 100%](fig/figRes23.png)] --- # Mean degree
.center[![:scale 100%](fig/figRes24.png)] --- # Mean degree .small[[Piechnik *et al.*, *Oikos*, 2008.](https://www.jstor.org/stable/3544109)]
.center[![:scale 100%](fig/figRes25.png)] --- # An Energetic Theory of Isand Biogeography
-- ## - TTIB / MTE (or DEB)
-- ## - Better quantification
-- ## - Theoretical fundations of NDMs --- # New insights
.center[![:scale 85%](fig/Hatton.png)] --- # New insights
.center[![:scale 95%](fig/figdem7.png)]