class: middle, title-slide <!-- top logo (comment to remove or edit on `conf/css/style.css:23`) --> <div class="lab-logo"></div> <!-- <div class="uni-logo"></div> --> # Effects of temperature on trophic interactions <hr width="65%" align="left" size="0.3" color="orange"></hr> ## A perspective across different time scales, spatial scales and organizational levels ### Azenor Bideault <br> Dominique Gravel & Michel Loreau <br> <!-- [<i class="fa fa-github fa-lg" style="color:#e7e8e2"></i> Azenor/talk_Econet2021](https://github.com/Azenor/talk_Econet2021) --> [<i class="fa fa-twitter fa-lg" style="color:#e7e8e2"></i> @Azenor_Bideault](https://twitter.com/Azenor_Bideault) --- # Ecosystems vary in space <br> .center[  <br> Species are different...] --- # Important gradients across latitudes .center[ ] .cite[From Albouy et al [2019]] --- class: center # Is there a latitudinal gradient in trophic interaction ?  --- # Importance of trophic interactions in ecosystem functioning .center[  <br> Trophic cascades : predators regulate herbivores, enhancing primary producers abundance .cite[Estes et al [2011]]] --- # Trophic control .center[ **Regulation through consumers or resources** ] <br> - Dynamical property of consumer-resource systems - Defined from species biological rates (e.g. interaction rate) --- # Variation in trophic control across latitudes .center[] - Predator-prey cycles in the arctic - Stronger herbivory and insect predation in the tropics .center[**What drives these variations in trophic control?**] .cite[Schemske et al [2009]] --- class:middle, inverse, center # Does temperature drive a latitudinal gradient in trophic control? --- # Temperature induces a major environmental gradient .center[] --- # And affects many ecological processes .center[ **Cell** Metabolic rate] --- # And affects many ecological processes .center[ **Individuals** Biological rates] --- # And affects many ecological processes .center[ **Populations** Biological rates] --- # And affects many ecological processes .center[ **Communities** Trophic control] --- # The metabolic view of the world .center[] .center[**Metabolism controls higher orders ecological processes**] .cite[Gillooly et al [2001], Brown et al [2004]] --- # Latitudinal variation in trophic control .center[ **Can the allometric scaling of metabolism explain the large scale variation in trophic control?**] --- # Latitudinal variation in trophic control .center[] - Evolutionary processes might alter the relationship between biological rates and temperature at the population level - At large scale, other variables might affect trophic control : latitudinal gradient in species richness and body mass --- # What's on the menu? .center[] <br> 1. Temperature dependence of biological rates - **Thermal adaptation of growth rate in wild bacterial strains** --- # What's on the menu? .center[] <br> 1. Temperature dependence of biological rates - **Thermal adaptation of growth rate in wild bacterial strains** 2. Temperature dependence of trophic control for pairs of consumer-resource - **Theory based on the temperature dependence of biological rates** --- # What's on the menu? .center[] <br> 1. Temperature dependence of biological rates - **Thermal adaptation of growth rate in wild bacterial strains** 2. Temperature dependence of trophic control for pairs of consumer-resource - **Theory based on the temperature dependence of biological rates** 3. Is there a latitudinal gradient in trophic control and what are its drivers ? - **Trophic control in fish food webs at large scales** --- class: inverse, middle, center # Thermal adaptation of growth rate in wild bacterial strains --- # Biological rates & temperature .center[ <br> For ectothermic organisms <br> How does this relationship vary under thermal adaptation?] --- # Evolutionary processes : local adaptation .center[ **Biological rates are optimal at the local temperature**] --- # Metabolic theory : hotter is faster ... .center[ **Allometric scaling : increase in biological rates with temperature, strong kinetic constraints**] --- # Metabolic theory : ... and colder is slower .center[ **Allometric scaling : increase in biological rates with temperature, strong kinetic constraints**] --- # Bacteria .center[Are useful for many things!  <br> **Key role in many ecological processes**] - Fast reproduction & small size - Easily culturable in the lab - Extrapolate results to other organisms .center[Experiment on thermal adaptation of growth rate in wild bacterial strains] --- # Population growth rate <br> .center[A key biological process & temperature dependent & easily measurable <br> ] --- # Evolutionary experiment .center[] --- # Evolutionary experiment .center[] --- # Evolutionary experiment .center[] --- # Metabolic theory : Hotter is better! <br> .center[ ] --- # Metabolic theory : Hotter is better! <br> .center[ ] --- # Metabolic theory : Hotter is better! <br> .center[ ] --- # Metabolic theory : Hotter is better! <br> .center[  <br> **Increase in growth rate with temperature, no matter the temperature of evolution**] --- # To sum-up : Hotter is better! .center[ ] <br> Support for : - Limited local adaptation - Metabolic theory : allometric scaling of growth rate <br> But : - One experiment - Bacteria .cite[Allen et al [2002], Gilloly et al [2007]] --- # To sum-up : Hotter is better! .center[ ] <br> Support for : - Limited local adaptation - Metabolic theory : allometric scaling of growth rate <br> .center[Suggesting kinetic constraints on biological rates : increase in biological rates with temperature across latitudes] .cite[Allen et al [2002], Gilloly et al [2007]] --- # From populations to consumer-resource interactions .center[ <br> **How does the temperature dependence of population biological rates affect trophic control?**] --- class: middle, inverse, center # Theory on the temperature dependence of trophic control --- # How to measure trophic control? .center[  **Models are useful** .font60[(more than bacteria?)] <br> Describe consumer-resource systems and measure their dynamical properties such as trophic control] --- # Model of consumer-resource system `\begin{align} \dfrac{dB_i}{dt} &= \textrm{production} \\ \frac{dB_i}{dt} &= g_iB_i \end{align}` <br> .pull-left[ - B biomass - g<sub>i</sub> growth rate] .pull-right[  ] --- # Model of consumer-resource system `\begin{align} \dfrac{dB_i}{dt} &= \textrm{production} - \textrm{predation losses} \\ \frac{dB_i}{dt} &= g_iB_i + \epsilon A_{ij} B_iB_j - A_{ki} B_iB_k \end{align}` <br> .pull-left[ - B biomass - g<sub>i</sub> net growth rate - A<sub>ij</sub> interaction matrix - *ϵ* conversion efficiency] .pull-right[  ] --- # Model of consumer-resource system `\begin{align} \dfrac{dB_i}{dt} &= \textrm{production} - \textrm{predation losses} \\ \frac{dB_i}{dt} &= g_iB_i + \epsilon A_{ij} B_iB_j - A_{ki} B_iB_k \end{align}` <br> .pull-left[ - B biomass - g<sub>i</sub> net growth rate - A<sub>ij</sub> interaction matrix - *ϵ* conversion efficiency] .pull-right[  ] --- # Model of consumer-resource system `\begin{align} \dfrac{dB_i}{dt} &= \textrm{production} - \textrm{predation losses} - \textrm{internal losses} \\ \frac{dB_i}{dt} &= g_iB_i + \epsilon A_{ij} B_iB_j - A_{ki} B_iB_k - D_iB_i^2 \end{align}` <br> .pull-left[ - B biomass - g<sub>i</sub> net growth rate - A<sub>ij</sub> interaction matrix - *ϵ* conversion efficiency - D<sub>i</sub> self regulation] .pull-right[  ] --- # Activation energy = thermal sensitivity .pull-left[.center[]] .pull-right[ <br><br> `\(\huge b_i = b_{0_i}e^{-E_i/kT}\)` <br><br> * b<sub>0</sub>, k constants * T temperature * **E activation energy** ] .center[**How does this temperature dependence translate into trophic control?**] --- # Measure of trophic control .center[λ describes the feedback of a trophic level on itself through its predators ] .cite[Barbier & Loreau [2019]] --- # Measure of trophic control .center[λ describes the feedback of a trophic level on itself through its predators ] .cite[Barbier & Loreau [2019]] --- # Temperature dependence .center[Of biological rates ] --- # Thermal mismatches in biological rates .center[**Determine trophic control**] `\(λ = \dfrac{ϵA_{21}}{D_1D_2}\)` Activation energy : <br> `\(E_\lambda = E_ϵ + 2(E_A-E_{D_2}) + E_{D_2} - E_{D_1}\)` .center[] --- # Database of activation energies .center[] .pull-left[ * Various species (ectotherm) * Taxonomic groups * Habitat * Diet] <br> .cite[Dell et al [2011], Burnside et al [2014], Fussman et al [2014]] --- # Temperature dependence of trophic control .center[ ] - Temperature increases top-down control in aquatic systems - No effect of temperature on terrestrial ecosystems - Difference between terrestrial and aquatic communities - General picture but large variation accross taxonomic groups --- # To sum-up .center[] - Derive a theory describing the temperature dependence of trophic control - Thermal mismatches in biological rates determine trophic control - Temperature induces more top-down (predator) control in aquatic systems --- # From consumer-resource systems to food webs at large scale .center[] <br> .center[ **Is there a latitudinal gradient in trophic control in fish food webs?** <br> **Is it driven by a direct effect of temperature on biological rates?**] --- class: inverse, middle, center # Latitudinal variation in trophic control --- # Latitudinal gradients .center[**Temperature** <br> ] --- # Other important latitudinal gradients <br> .center[  <br> Which might also affect trophic control] --- # Method .center[] <br> .cite[Albouy et al [2019], Irigoien et al [2014]] --- # Parameterize complex food web models .center[] - Temperature dependence of biological rates - Same activation energy for every species - Self-regulation : A key but still too mysterious parameter - Estimation from assumptions on coexistence and stability and biomass scaling laws .center[Predictions of trophic control knowing model assumptions] --- # Gradient in trophic control .center[  **Increase in top-down control toward the poles**] --- # Latitudinal variation .center[ Increase in top-down control toward the poles] --- # Latitudinal variation .center[ Temperature and species richness peaks in the tropics, smaller body mass] --- # Relative contributions .center[ **Trophic control is mainly driven by species richness** ] --- # To sum-up .center[**Latitudinal variation in trophic control, driven by species richness**] .center[ ] - Species rich food webs around the equator more bottom-up controlled - Food webs at high latitudes more top-down controlled (control by predator, trophic cascades, cycles) - Weak effect of temperature on trophic control in complex food webs --- # To sum-up .center[**Latitudinal variation in trophic control, driven by species richness**] .center[ ] Limitations : - Limited data available - No variation in activation energies (but same taxonomic group) - Exponential vs unimodal functions - Model assumptions and parameters --- class: inverse, center, middle # Discussion --- # Take-home messages .center[ ] <br> 1. Support for metabolic theory and limited local adaptation -- 2. Derive a theory for the temperature dependence of trophic control - Increase in top-down control in aquatic systems -- 3. Latitudinal gradient in trophic control in fish food webs - Decrease in top-down control toward the equator - Mostly driven by species richness --- # Latitudinal variation in trophic control .center[] - Stronger top-down control at high latitudes : predator-prey cycle - Weaker top-down regulation in tropical food webs - Quantifying interaction strength - Strong effect of species richness : weak interactions are assumed to promote stability in complex systems .center[**Importance of species richness**] .cite[McCann et al [1998], Schemske et al [2009]] --- # Indirect effect of temperature? .center[  **Species richness = indirect effect of temperature?**] <br> Rates of genetic divergence and speciation governed by metabolic rates? <br> Opposite effects of temperature : - direct increase in top-down control through increasing biological rates - indirect decrease in top-down control through increasing species richness .cite[Allen et al [2006]] --- # Complexity of temperature effects .center[  **Explain latitudinal variation in food web dynamics** <br>] --- # And predict the impacts of climate change .center[] - Bacteria seem to like warm weather ! - Climate warming can alter trophic control but strong effects of species richness at large scale - Indirect effects of warming -- <br> .center[**Global change : climate change & biodiversity loss (& ...)**] --- class: inverse .pull-left1[ <br> .font100[**"An ecologist is often balancing the search for simplifying theories with the recognition of the complexity of nature"** - Charles Elton] <br> **Special thanks to** - You for listening - My supervisors Dominique and Michel - Jury members : Sophie, Marco and John P. Delong - Committee members : Marco and Arnaud - Great collaborators : Matthieu, Yuval, Nuria, Arnaud, Stéphanie - Lab mates in Sherbrooke and Moulis - Housemates, friends and family - Will and Steve for hosting me during my stay! ] .pull-right1[ <br>  ] --- class: middle, inverse, center # Supplementary slides --- class: middle, inverse, center # Bacteria --- # Heat maps .center[ ] --- # TPC .center[ ] --- # Difference in growth rate .center[ ] --- # Replicates .center[ ] --- class: inverse, middle, center # Temperature dependence of trophic control and biomass distribution --- # Results .center[ ] --- # Results .center[ ] --- # Results .center[ ] --- # Results .center[ ] --- class: inverse, middle, center # Fish food webs --- # Self-regulation .font80[An important but not well known parameter] <br> .center[**Intraspecific density dependent regulation** <br> A population’s growth rate is negatively affected by its own population density] <br> Examples : - territoriality - infanticide - intra-guild predation - competition for light <br> .center[**Important to match stability levels observed in nature**] --- # Estimation of species biomass .center[Self-regulation is completely unknown...<br> Biomass can be inferred from allometric relationship] .center[ ] .cite[Hatton et al [2019]] --- # Method to estimate self-regulation <br> `\begin{align} \frac{dB_i}{dt} = g_iB_i + \sum_j \epsilon A_{ij} B_iB_j-\sum_k A_{ki} B_iB_k - D_iB_i^2 \end{align}` <br><br> .center[ - using estimations of biological rates and biomass - allow coexistence - equilibrium] <br><br> .center[**Simulate the dynamics of communities and measure some dynamical properties**] --- # Metrics of community dynamics <br><br> **Variability : temporal biomass variance in response to stochastic pertubations (community average)** `\begin{align} \mathcal{V} = tr(C) \end{align}` `\(C\)` covariance matrix, solution of the Lyapunov equation `\(JC+CJ^T = \mathbb I\)` with `\(J\)` Jacobian matrix .cite[Arnoldi et al [2019]] --- # Measures of community dynamics <br><br> **Collectivity : importance of indirect interactions (collectivity = 1, a change in species abundance affect other species far in the network)** `\begin{align} \phi = \rho(M_{ij}) = \max_i|\lambda_i(M)| \end{align}` spectral radius of `\(M_{ij} = A_{ij}/D_i\)`, `\(\lambda_i(M)\)` is the ith eigenvalue of matrix `\(M\)` .cite[Arnoldi et al [in prep]] --- # Simulate warming <br><br> - Direct effect of warming on species biological rates - Compute the relative change in community metrics `\begin{align} \Delta(x) = \textrm{log}_{10}(x_{warm}) - \textrm{log}_{10}(x) \approx (x_{warm} - x)/x \end{align}` --- class: inverse, middle, center # Results --- # Latitudinal variation <br> .center[] --- # Moderate effect on community properties <br> .center[] --- # Stronger effect at the species level .center[]