class: top, left, inverse, title-slide # Mapping biodiversity changes across
spatial and temporal scales ##
PhD Presentation ###
Student: François Leroy
Supervisor: Petr Keil ### Czech Univeristy of Life Sciences
Prague --- # A reminder about biodiversity .pull-left[ * A the basis of many ecosystem services <br> * Globally decreasing but local loss is not certain (Dornelas *et al* 2014) <br> * Several species-based facets of biodiversity: species richness, species diversity, `\(\alpha\)`, `\(\beta\)`, `\(\gamma\)` diversity, trends... ] .pull-right[ <img src="data:image/png;base64,#images/Forest_fruits_from_Barro_Colorado.png" width="1333" height="400px" /> .credit[BCI fruits, Panama] ] --- # A reminder about biodiversity .pull-left[ <br> * Biodiversity is an extensive variable = defined by space and/or time <br> * Spatial and temporal scales can highly influence biodiversity and its dynamic ] .pull-right[ <img src="data:image/png;base64,#images/Forest_fruits_from_Barro_Colorado.png" width="1333" height="400px" /> .credit[BCI fruits, Panama] ] .center[**But what is the link between space, time and biodiversity?**] --- class: inverse, center, middle Focus on ## Species Richness --- # Species richness and spatial scale : the SAR .pull-left[ <br><br> - **SAR** = Species Area Relationship (Arrhenius 1921) <br><br><br> - Linear on a log-log scale <!-- <br> --> <!-- - The slope indicates the spatial `\(\beta-diversity\)` --> <!-- <br> --> <!-- - Can be used to extrapolate species richness (*e.g.* Kunin *et al.* 2018) --> ] .pull-right[ <img src="data:image/png;base64,#images/sar.png" width="800" height="430px" /> .credit[Brown *et al.* 2007] ] --- # Species richness and temporal scale: the STR .pull-left[ <br><br> - **STR** = Species-Time Relationship <br><br><br> - Can also be well described by a power law <!-- <br> --> <!-- - Emerges from both sampling and ecological processes --> <!-- <br> --> <!-- .center[**And... we don't know much more about it**] --> ] .pull-right[ <img src="data:image/png;base64,#images/str.png" width="552" height="430px" /> .credit[STR of the Breeding Bird Survey for different North American states, White 2004] ] --- # Species richness, space and time: the STAR .pull-left[ <br> - **STAR** = Species-Time-Area Relationship <!-- <br> --> <!-- - Results from both environmental variability and biological processes --> <br><br><br> <!-- The STAR raises the question: --> <!-- <br> --> .center[**Temporal and spatial scales highly drive species richness**] ] .pull-right[ <img src="data:image/png;base64,#images/star.png" width="352" /> .credit[Plant species richness as a function of interacting space and time, Adler & Lauenroth 2003] ] --- class: inverse, center, middle What about space, time and... ## Species richness trends ? --- # Biodiversity changes and spatial scales .pull-left[ * According to the taxa: .center[*"Species richness change can increase, decrease, reverse or be unimodal accross spatial scales."*] * For North American birds, larger spatial scales seem to increase positively the species richness (Oikos, Chase *et al* 2019) <br> -------- * Temporal <span style="color: grey;">dissimilarity</span> and <span style="color: red;">turnover</span>, <span style="color: orange;">extinction</span> and <span style="color: blue;">colonization</span> seem to decrease with increasing spatial scales (Glob. Ecol. Biogeogr., Jarzyna *et al.* 2015) ] .pull-right[ .center[ <img src="data:image/png;base64,#images/chase_2019.PNG" width="75%" /> ] <img src="data:image/png;base64,#images/jarzyna_2015.PNG" width="1289" height="3%" /> ] --- # Biodiversity changes and temporal scales... <br><br><br> .center[...so far, nothing in sight in the scientific litterature] --- class: inverse, center, middle # Problematic: What are the links between species-richness trends and spatio-temporal scales? -- <br><br><br> <b>Taxon:</b> Birds (many long time series, well identified, able to move after perturbations...) <b>Location:</b> At first Czech Republic, then western Europe, north America... <b>Methods:</b> Tree based Machine learning approaches (Random Forests or Boosted Regression Trees) --- class: inverse, center, middle # Goal Use heterogeneous avian biodiversity datasets to model species richness trends across continuums of space and time scales .center[ <img src="data:image/png;base64,#images/star.png" width="50%" /> ] --- # Avian biodiversity datasets <br> We need heterogeneous datasets with: * Time series (for the trend) * Several spatial scales * Several temporal scales <br><br> So far, I worked with 2 datasets: 1. The atlas data from the Czech Society for Ornithology (Česká společnost ornitologická). Courtesy of Vladimír Bejček, Karel Šťastný and Ivan Mikuláš. 2. Local time series from the Breeding Bird Survey (Jednotný program sčítání ptáků). Courtesy of Jiří Reif. --- # The Atlas dataset .pull-left[ 4 time periods, 3 different time spans: * M1 = 1973-1977 (5 years) * M2 = 1985-1989 (5 years) * M3 = 2001-2003 (3 years) * M4 = 2014-2017 (4 years) ] .pull-right[ Spatial scales ranging from less than 100 Km `\(^2\)` to 80 000 Km `\(^2\)` (the entire Czech Republic) ] --- # The Atlas dataset ![](data:image/png;base64,#index_files/figure-html/unnamed-chunk-13-1.png)<!-- --> --- # The JPSP dataset * Local time series * 350 transects * 20 census points per transect * From 1982 to 2020 * At least 2 censuses per transect and per year * 4 different spatial scales * Temporal scales ranging from 0.5 year to 5 years --- # The JPSP dataset
--- class: inverse, center, middle # Pilot results --- # Species richness trend across spatial scales * For each spatial scale, we computed the species richness trend (slope of linear regression) * 3 points in time (1987, 2002, 2015) * Harmonization of the two datasets --- # Species richness trend across spatial scales <img src="data:image/png;base64,#images/atlas_maps_boxplot.png" width="95%" /> --- # Species richness trend across spatial scales <img src="data:image/png;base64,#images/boxplot.png" width="95%" /> --- # Species richness trend across spatial scales .pull-left[ * Increasing species richness trend with spatial scale * Coherent with Chase *et. al* 2019 * Easier extirpation at smaller scales * Lower proportion of extinction with increasing scales (Keil *et. al* 2018) * More habitat heterogeneity at larger scales ] .pull-right[ <br> <img src="data:image/png;base64,#images/boxplot.png" width="95%" /> ] .center[ <br> **Question:** is this result observed for a continuum of spatial scales? ] --- class: inverse, center, middle # Next step --- # Random Forest Machine learning approach allows me to: 1. Understand the drivers of species richness changes 2. Predict the species richness Predictions will allow me to fill the boxplot gaps, spatial and temporal gaps of the datasets <br> **Formula:** ```r randomForest(sr ~ Lat + Long + AREA + Date + polypoint_ratio + time_span) ``` --- # Partial plots .pull-left[ .center[**The SAR**] <img src="data:image/png;base64,#images/sar_rf.jpg" width="100%" /> ] .pull-right[ .center[**The STR**] <img src="data:image/png;base64,#images/str_rf.jpg" width="100%" /> ] --- # Partial plots .pull-left[ .center[**The STAR**] <img src="data:image/png;base64,#images/star_rf.png" width="100%" /> ] .pull-right[ .center[<br>] <img src="data:image/png;base64,#images/str_overtime.png" width="100%" /> ] --- # Predicitons * For <span style="color: blue;">50 `\(Km²\)`</span> and <span style="color: blue;">10 000 `\(Km²\)`</span> .pull-left[ <br> <img src="data:image/png;base64,#images/50sqkm.png" width="100%" /> ] .pull-right[ <br> <img src="data:image/png;base64,#images/10000sqkm.png" width="100%" /> ] --- # Predicitons * For <span style="color: blue;">50 `\(Km²\)`</span> and <span style="color: blue;">10 000 `\(Km²\)`</span> .center[ <img src="data:image/png;base64,#images/boxplot_with_predictions.png" width="87%" /> ] --- # Next steps <br> * Take into account the sampling effort <br> * Take into account environmental covariates to understand at which scales they interact with biodiversity dynamic <br> * Explore the link with temporal scales <br> * Enlarge the model to western europe <br> * Study other biodiversity metrics and other taxa (lepidopterans, amphibians...) --- class: inverse, center, middle # Thank you for your attention .footnote[ Email: leroy@fzp.czu.cz ]