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<title>Hotspot identification using a relative frequency distribution approach</title>
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<h1 class="title toc-ignore">Hotspot identification using a relative frequency distribution approach</h1>
<h4 class="author"><em>PJ Bouchet</em></h4>
<h4 class="date"><em>2019-01-18</em></h4>
<p>This small vignette illustrates the use of custom functions for identifying ‘hotspots’ in a spatial variable of interest.</p>
<p>The code is based on the frequency distribution approach proposed by Bartolino et al. (2011)<a href="#fn1" class="footnoteRef" id="fnref1"><sup>1</sup></a> and applied in Bouchet et al. (2017).<a href="#fn2" class="footnoteRef" id="fnref2"><sup>2</sup></a></p>
<p>The required libraries and options are specified below.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(fANCOVA)
<span class="kw">library</span>(raster)
<span class="kw">library</span>(virtualspecies)
<span class="kw">library</span>(tidyverse)
<span class="kw">options</span>(<span class="dt">tibble.width =</span> <span class="ot">Inf</span>) <span class="co"># All tibble columns shown</span>
<span class="kw">options</span>(<span class="dt">pillar.neg =</span> <span class="ot">FALSE</span>) <span class="co"># No colouring negative numbers</span>
<span class="kw">options</span>(<span class="dt">pillar.subtle =</span> <span class="ot">TRUE</span>)
<span class="kw">options</span>(<span class="dt">pillar.sigfig =</span> <span class="dv">4</span>)</code></pre></div>
<p>Below is a simple simulated example using WorldClim data. WorldClim (www.worldclim.org) freely provides gridded climate data (temperature and precipitations) for the entire World. Here, we generate a virtual tropical species (ie. living in hot and humid environments), whose response to two environmental variables, the annual mean temperature bio1 and annual mean precipitation bio2, is pre-determined. Code adapted from: <a href="http://borisleroy.com/files/virtualspecies-tutorial.html#input-data" class="uri">http://borisleroy.com/files/virtualspecies-tutorial.html#input-data</a></p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co"># Downloads WorldClim data</span>
worldclim <-<span class="st"> </span><span class="kw">getData</span>(<span class="st">"worldclim"</span>, <span class="dt">var =</span> <span class="st">"bio"</span>, <span class="dt">res =</span> <span class="dv">10</span>)
<span class="co"># Gaussian functions of bio1 and bio12</span>
my.parameters <-<span class="st"> </span><span class="kw">formatFunctions</span>(<span class="dt">bio1 =</span> <span class="kw">c</span>(<span class="dt">fun =</span> <span class="st">"dnorm"</span>, <span class="dt">mean =</span> <span class="dv">250</span>, <span class="dt">sd =</span> <span class="dv">50</span>),
<span class="dt">bio12 =</span> <span class="kw">c</span>(<span class="dt">fun =</span> <span class="st">"dnorm"</span>, <span class="dt">mean =</span> <span class="dv">4000</span>, <span class="dt">sd =</span> <span class="dv">2000</span>))
<span class="co"># Generates simulated species distributions</span>
simsp <-<span class="st"> </span><span class="kw">generateSpFromFun</span>(<span class="dt">raster.stack =</span> worldclim[[<span class="kw">c</span>(<span class="st">"bio1"</span>, <span class="st">"bio12"</span>)]], <span class="dt">parameters =</span> my.parameters,
<span class="dt">plot =</span> <span class="ot">TRUE</span>)</code></pre></div>
<p><img 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" /><!-- --></p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">
<span class="co"># For the sake of the example only extracts a small portion of that</span>
<span class="co"># distribution eg from South America</span>
simdist <-<span class="st"> </span>raster<span class="op">::</span><span class="kw">crop</span>(<span class="dt">x =</span> simsp<span class="op">$</span>suitab.raster, <span class="dt">y =</span> <span class="kw">as</span>(<span class="kw">extent</span>(<span class="kw">c</span>(<span class="op">-</span><span class="dv">51</span>, <span class="op">-</span><span class="dv">45</span>, <span class="op">-</span><span class="dv">15</span>,
<span class="op">-</span><span class="dv">5</span>)), <span class="st">"SpatialPolygons"</span>))
<span class="kw">plot</span>(simdist)</code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co"># Turns the raster into a data.frame object and manipulates values</span>
dat <-<span class="st"> </span>raster<span class="op">::</span><span class="kw">as.data.frame</span>(simdist, <span class="dt">xy =</span> T)
dat <-<span class="st"> </span>dat <span class="op">%>%</span><span class="st"> </span>purrr<span class="op">::</span><span class="kw">set_names</span>(., <span class="kw">c</span>(<span class="st">"longitude"</span>, <span class="st">"latitude"</span>, <span class="st">"z"</span>))
dat<span class="op">$</span>z =<span class="st"> </span><span class="kw">round</span>(dat<span class="op">$</span>z <span class="op">*</span><span class="st"> </span><span class="dv">100</span>, <span class="dv">0</span>)</code></pre></div>
<p>Next we define custom functions to calculate the cumulative relative frequency distribution function CRFD (as described in the Bartolino paper)</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">no.cumul <-<span class="st"> </span><span class="cf">function</span>(data, value) {
<span class="kw">return</span>(<span class="kw">length</span>(data[data <span class="op"><</span><span class="st"> </span>value]))
}
bartolino <-<span class="st"> </span><span class="cf">function</span>(df, var.name) {
<span class="co"># Converts var.name to a string</span>
var.name <-<span class="st"> </span><span class="kw">deparse</span>(<span class="kw">substitute</span>(var.name))
<span class="co"># Calculates x-axis [x = z / zm] and y-axis [y = M(x)/n] values</span>
df <-<span class="st"> </span>df <span class="op">%>%</span><span class="st"> </span><span class="kw">mutate_</span>(<span class="dt">x =</span> <span class="kw">paste</span>(var.name, <span class="st">"/max("</span>, var.name, <span class="st">")"</span>))
allx <-<span class="st"> </span>df <span class="op">%>%</span><span class="st"> </span><span class="kw">pull</span>(x)
df <-<span class="st"> </span>df <span class="op">%>%</span><span class="st"> </span>rowwise <span class="op">%>%</span><span class="st"> </span><span class="kw">mutate</span>(<span class="dt">y =</span> <span class="kw">no.cumul</span>(allx, x)<span class="op">/</span><span class="kw">nrow</span>(df)) <span class="op">%>%</span><span class="st"> </span><span class="kw">ungroup</span>()
<span class="kw">return</span>(df)
} <span class="co"># End function</span></code></pre></div>
<p>These functions can be applied to the data.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">dat.bart <-<span class="st"> </span><span class="kw">bartolino</span>(<span class="dt">df =</span> dat, <span class="dt">var.name =</span> z)</code></pre></div>
<p>Additional functions are needed to determine the highest x-value corresponding to a 45 degree tangent to the predicted loess curve.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">find.bartolino <-<span class="st"> </span><span class="cf">function</span>(loess.predictions) {
<span class="cf">for</span> (p <span class="cf">in</span> <span class="dv">3</span><span class="op">:</span>(<span class="kw">length</span>(loess.predictions) <span class="op">-</span><span class="st"> </span><span class="dv">1</span>)) {
slope.curve <-<span class="st"> </span>(loess.predictions[p <span class="op">+</span><span class="st"> </span><span class="dv">1</span>] <span class="op">-</span><span class="st"> </span>loess.predictions[p <span class="op">-</span><span class="st"> </span><span class="dv">1</span>])<span class="op">/</span>(loess.x[p <span class="op">+</span><span class="st"> </span>
<span class="st"> </span><span class="dv">1</span>] <span class="op">-</span><span class="st"> </span>loess.x[p <span class="op">-</span><span class="st"> </span><span class="dv">1</span>])
<span class="cf">if</span> (slope.curve <span class="op">>=</span><span class="st"> </span><span class="dv">1</span>) {
barto.x <-<span class="st"> </span>loess.x[p]
<span class="cf">break</span>
}
}
<span class="kw">return</span>(barto.x)
} <span class="co"># End function</span>
find.bartolino.y <-<span class="st"> </span><span class="cf">function</span>(loess.predictions) {
<span class="cf">for</span> (p <span class="cf">in</span> <span class="dv">3</span><span class="op">:</span>(<span class="kw">length</span>(loess.predictions) <span class="op">-</span><span class="st"> </span><span class="dv">1</span>)) {
slope.curve <-<span class="st"> </span>(loess.predictions[p <span class="op">+</span><span class="st"> </span><span class="dv">1</span>] <span class="op">-</span><span class="st"> </span>loess.predictions[p <span class="op">-</span><span class="st"> </span><span class="dv">1</span>])<span class="op">/</span>(loess.x[p <span class="op">+</span><span class="st"> </span>
<span class="st"> </span><span class="dv">1</span>] <span class="op">-</span><span class="st"> </span>loess.x[p <span class="op">-</span><span class="st"> </span><span class="dv">1</span>])
<span class="cf">if</span> (slope.curve <span class="op">>=</span><span class="st"> </span><span class="dv">1</span>) {
barto.y <-<span class="st"> </span>loess.predictions[p]
<span class="cf">break</span>
}
}
<span class="kw">return</span>(barto.y)
} <span class="co"># End function</span></code></pre></div>
<p>A LOESS model can be fitted to the CRFD points, and the x-value cutoff identified from the resulting predictions.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co"># LOESS smoothing - with automated span selection based on AICc or GCV The</span>
<span class="co"># degree of smoothing can also be selected manually using user.span</span>
loess.x <-<span class="st"> </span><span class="kw">rev</span>(<span class="kw">seq</span>(<span class="dv">0</span>, <span class="dv">1</span>, <span class="fl">0.001</span>))
loessmod.n <-<span class="st"> </span>fANCOVA<span class="op">::</span><span class="kw">loess.as</span>(dat.bart<span class="op">$</span>x, dat.bart<span class="op">$</span>y, <span class="dt">degree =</span> <span class="dv">0</span>, <span class="dt">criterion =</span> <span class="kw">c</span>(<span class="st">"aicc"</span>,
<span class="st">"gcv"</span>)[<span class="dv">1</span>], <span class="dt">user.span =</span> <span class="ot">NULL</span>, <span class="dt">plot =</span> T)
lo.preds.n <-<span class="st"> </span><span class="kw">predict</span>(loessmod.n, loess.x)
xbest <-<span class="st"> </span><span class="kw">find.bartolino</span>(lo.preds.n)
ybest <-<span class="st"> </span><span class="kw">find.bartolino.y</span>(lo.preds.n)
<span class="kw">abline</span>(<span class="dt">v =</span> xbest, <span class="dt">col =</span> <span class="st">"orange"</span>, <span class="dt">lty =</span> <span class="dv">2</span>)</code></pre></div>
<p><img 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" /><!-- --></p>
<p>Finally, hotspots are simply those sites with an x value higher than the threshold.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">dat.hot <-<span class="st"> </span>dat.bart <span class="op">%>%</span><span class="st"> </span><span class="kw">filter</span>(x <span class="op">>=</span><span class="st"> </span>xbest)
<span class="co"># Converts to SpatialPoints df</span>
hot.pts <-<span class="st"> </span>dat.hot <span class="op">%>%</span><span class="st"> </span>dplyr<span class="op">::</span><span class="kw">select</span>(longitude, latitude, z) <span class="op">%>%</span><span class="st"> </span><span class="kw">SpatialPointsDataFrame</span>(<span class="dt">coords =</span> <span class="kw">cbind</span>(.<span class="op">$</span>longitude,
.<span class="op">$</span>latitude), <span class="dt">data =</span> .)
<span class="co"># Visualisation</span>
<span class="kw">plot</span>(simdist)
<span class="kw">plot</span>(hot.pts, <span class="dt">add =</span> T)</code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<div class="footnotes">
<hr />
<ol>
<li id="fn1"><p>Bartolino V, Maiorano L, Colloca F. 2011. A frequency distribution approach to hotspot identification. Population Ecology, 53(2): 351-359<a href="#fnref1">↩</a></p></li>
<li id="fn2"><p>Bouchet et al. 2017. Continental-scale hotspots of pelagic fish abundance inferred from commercial catch records. Global Ecology and Biogeography, 26(10): 1098-1111.<a href="#fnref2">↩</a></p></li>
</ol>
</div>
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