10506621Displacement Model: Foraging SeabirdsEdited by Drew.110013572generic_information_pageund1450791718150608693500150608693521- <p>This is a model, written in R, to simulate the effects of offshore wind farms upon seabird foraging behaviour, and the ultimate consequences of this for adult and chick survival.</p>
<p>It is called the “simplified” model to distinguish it from the displacement model that has already been developed by CEH which is more biologically realistic in a number of ways, but substantially more computationally-intensive to run.</p>
<p>The model has been designed for use with four specific proposed offshore wind farms in the Forth-Tay region, and for use with five specific species (guillemot, kittiwake, puffin, gannet and razorbill). Much of the code can be readily-applied to different species, wind farms and SPAs, but some cannot – we have attempted to make the code as generic as possible, but it does not, and was not designed to, provide general code for modelling the effects of any wind farm in any geographical area. The model can be downloaded from the table below.</p>
filtered_html<p>This is a model, written in R, to simulate the effects of offshore wind farms upon seabird foraging behaviour, and the ultimate consequences of this for adult and chick survival.</p>
<p>It is called the “simplified” model to distinguish it from the displacement model that has already been developed by CEH which is more biologically realistic in a number of ways, but substantially more computationally-intensive to run.</p>
<p>The model has been designed for use with four specific proposed offshore wind farms in the Forth-Tay region, and for use with five specific species (guillemot, kittiwake, puffin, gannet and razorbill). Much of the code can be readily-applied to different species, wind farms and SPAs, but some cannot – we have attempted to make the code as generic as possible, but it does not, and was not designed to, provide general code for modelling the effects of any wind farm in any geographical area. The model can be downloaded from the table below.</p>
- 41721guillemot_SNH.jpgpublic://guillemot_SNH.jpgimage/jpeg7099811458826230image
- Several Guillemots at a cliff edgeSeveral Guillemots at a cliff edge
- Guillemot - Copyright © SNHGuillemot - Copyright © SNH
<_drafty_revision_requested>FIELD_LOAD_CURRENTGuillemot - Copyright © SNHSeveral Guillemots at a cliff edge800532 - 13614
- 956
- 47
- 950
- 951
- 630
- <p><strong>Technical Details of the Model</strong></p>
<p>This simplified model includes three options for quantifying the magnitude of barrier effects. One option is to assume that they come from a normal distribution with mean 20 km and standard deviation 5 km; this corresponds to the way that barrier effects are specified in the full model. The remaining two options assume that the bird will incur an additional flight cost by flying around the wind farm rather than straight through it and quantify this additional cost by assuming that the wind farm is circular. The two options specify the radius of the circle in two ways:</p>
<ol>
<li>To ensure that the set of bearings from the SPA that encounter the circle is the same that encounter the actual wind farm; or</li>
<li>To ensure that the area of the circle is the same as that of the actual wind farm.</li>
</ol>
<p><strong>Input Files</strong></p>
<p>The model requires six input files; one file to provide species-specific information about the spatial distribution of the species within the region of interest, one file to provide parameter values for the model, and four files to provide meta-information.</p>
<p>The four meta-information files contain:</p>
<p>colonies.csv : locations of each colony (with columns ‘colony’, ‘longname’, ‘long’, ‘lat’)</p>
<p>colonysize.csv : size of each colony, in terms of number of pairs (with columns ‘SPA’, ‘Colony’, ‘Guillemot’, ‘Razorbill’, ‘Kittiwake’, ‘Puffin’, ‘Gannet’). Note that SPAs may contain more than one colony.</p>
<p>wfinfo.csv : locations, on the 0.5 x 0.5 km GEBCO grid, that are contained within the core and buffer regions for each wind farm. Columns are: ‘WFcode’, ‘Longitude’, ‘Latitude’. Ten options are currently used for WFcode: ‘IC-footprint’ (Inchcape footprint), ‘IC-buffer’ (Inchcape buffer), and so on for NnG, R3A, R3B and R3AB.</p>
<p>wfstats.csv : summaries of the relationship between each wind farm and each SPA. Columns are: SPA, WindFarm, Dist, AngleMid, large.anglerange, large.radius, large.MAD, small.anglerange, small.radius, small.MAD. ‘Dist’ is the distance, in km, between the central colony of the SPA and the centre of the wind farm. The remaining columns refer to the sets of bearings from the SPA that would include the wind farm.</p>
<p>The parameter.csv file contains parameter values to use in running the displacement model – an example is provided. Information is required for all rows and all species. The ‘Version’ column is used when performing sensitivity analysis, and should be left blank otherwise.</p>
<table border="1">
<thead>
<tr>
<th scope="col">
<p><strong>Input file</strong></p>
</th>
<th scope="col">
<p><strong>Specific to a particular set of colonies?</strong></p>
</th>
<th scope="col">
<p><strong>Specific to a particular set of wind farms?</strong></p>
</th>
<th scope="col">
<p><strong>Specific to a particular species or set of species?</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>colonies.csv</p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p> </p>
</td>
<td>
<p> </p>
</td>
</tr>
<tr>
<td>
<p>colonysize.csv</p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p> </p>
</td>
<td>
<p> </p>
</td>
</tr>
<tr>
<td>
<p>wfinfo.csv</p>
</td>
<td>
<p class="rtecenter"> </p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p> </p>
</td>
</tr>
<tr>
<td>
<p>wfstats.csv</p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p> </p>
</td>
</tr>
<tr>
<td>
<p>parameters.csv</p>
</td>
<td>
<p> </p>
</td>
<td>
<p class="rtecenter"> </p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
</tr>
<tr>
<td>
<p>spatial.csv</p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p class="rtecenter"> </p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
</tr>
</tbody>
</table>
<p><strong>Model Functions</strong></p>
<p>Three functions are used to directly run the model and process the output; the actual calculations are performed by a number of additional functions, but these are not called directly by the user.</p>
<p>“<strong>vsdm.runmodel</strong>” runs the model for a single set of parameter values. The arguments are:</p>
<p> dat : spatial distribution of the species</p>
<p> species : species name</p>
<p> meta : meta information about SPAs and wind farms</p>
<p> pars.full : parameter values</p>
<p> pars.version : which version of the parameters to use (default is to use pars.version=0, which corresponds to none of the alternative versions being used)</p>
<p> ppop : which proportion of the population to use for simulation (default is to use ppop = 1, which corresponds to 100% of the population)</p>
<p> min.prey.adjust : ratio to use for adjusting minimum prey values</p>
<p> seedval.location : random seeds to use for simulating locations; set automatically if not specified</p>
<p> seedval.behaviour : random seed to use for simulation foraging behaviour; set automatically if not specified</p>
<p>“<strong>vsdm.sensitivity</strong>” runs the model for all parameter sets listed in the ‘parameters.csv’ file. The arguments are identical to those for “<strong>vsdm.runmodel</strong>” except that ‘pars.version’ is no longer an option (since the model is now run for all versions).</p>
<p>“<strong>getsummary.zones</strong>” summarizes the output from “<strong>vsdm.sensitivity</strong>” in a format that can be used to create a CSV file (spreadsheet). The sole argument is ‘out’, the output from running "<strong>vsdm.sensitivity</strong>".</p>
<p><strong>Example</strong></p>
<p>The following contains the R code used to run the analysis for kittiwake.</p>
<p>setwd("~/Work/Project/CEH/Displacement/SimplifiedModel/CurrentModel/")</p>
<p>source("Simplified-Displacement-Model-Version17.R")</p>
<p>pars.full <- (read.csv("Parameters/parameters-gps.csv"))[,3:9]</p>
<p>meta <- list(wf = read.csv("Meta/wfinfo.csv"), colony = read.csv("Meta/colonies.csv"), colonysize = read.csv("Meta/colonysize.csv"), wfstats = read.csv("Meta/wfstats.csv"))</p>
<p>levels(meta$colony$colony) <- c("ForthIslands", "Boddam", "FAR", "Fowlsheugh", "ForthIslands", "StAbbsHead", "TPL")</p>
<p>levels(meta$wfstats$SPA)[3] <- "ForthIslands"</p>
<p>## Species-specific part :</p>
<p>dat <- read.csv("/tmpshare/adam/projects/seabirds/Displacement/out-sixth/kittiwake.csv")</p>
<p>levels(dat$Site)[3] <- "ForthIslands"</p>
<p>out.kittiwake <- vsdm.sensitivity(dat, species = "Kittiwake", meta = meta, pars.full = pars.full, ppop = 1/3)</p>
<p> write.csv(getsummary.zones(out.kittiwake), file="Output/sensitivity-kittiwake.csv", quote=FALSE, row.names=FALSE)</p>
full_html<p><strong>Technical Details of the Model</strong></p>
<p>This simplified model includes three options for quantifying the magnitude of barrier effects. One option is to assume that they come from a normal distribution with mean 20 km and standard deviation 5 km; this corresponds to the way that barrier effects are specified in the full model. The remaining two options assume that the bird will incur an additional flight cost by flying around the wind farm rather than straight through it and quantify this additional cost by assuming that the wind farm is circular. The two options specify the radius of the circle in two ways:</p>
<ol>
<li>To ensure that the set of bearings from the SPA that encounter the circle is the same that encounter the actual wind farm; or</li>
<li>To ensure that the area of the circle is the same as that of the actual wind farm.</li>
</ol>
<p><strong>Input Files</strong></p>
<p>The model requires six input files; one file to provide species-specific information about the spatial distribution of the species within the region of interest, one file to provide parameter values for the model, and four files to provide meta-information.</p>
<p>The four meta-information files contain:</p>
<p>colonies.csv : locations of each colony (with columns ‘colony’, ‘longname’, ‘long’, ‘lat’)</p>
<p>colonysize.csv : size of each colony, in terms of number of pairs (with columns ‘SPA’, ‘Colony’, ‘Guillemot’, ‘Razorbill’, ‘Kittiwake’, ‘Puffin’, ‘Gannet’). Note that SPAs may contain more than one colony.</p>
<p>wfinfo.csv : locations, on the 0.5 x 0.5 km GEBCO grid, that are contained within the core and buffer regions for each wind farm. Columns are: ‘WFcode’, ‘Longitude’, ‘Latitude’. Ten options are currently used for WFcode: ‘IC-footprint’ (Inchcape footprint), ‘IC-buffer’ (Inchcape buffer), and so on for NnG, R3A, R3B and R3AB.</p>
<p>wfstats.csv : summaries of the relationship between each wind farm and each SPA. Columns are: SPA, WindFarm, Dist, AngleMid, large.anglerange, large.radius, large.MAD, small.anglerange, small.radius, small.MAD. ‘Dist’ is the distance, in km, between the central colony of the SPA and the centre of the wind farm. The remaining columns refer to the sets of bearings from the SPA that would include the wind farm.</p>
<p>The parameter.csv file contains parameter values to use in running the displacement model – an example is provided. Information is required for all rows and all species. The ‘Version’ column is used when performing sensitivity analysis, and should be left blank otherwise.</p>
<table border="1">
<thead>
<tr>
<th scope="col">
<p><strong>Input file</strong></p>
</th>
<th scope="col">
<p><strong>Specific to a particular set of colonies?</strong></p>
</th>
<th scope="col">
<p><strong>Specific to a particular set of wind farms?</strong></p>
</th>
<th scope="col">
<p><strong>Specific to a particular species or set of species?</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>colonies.csv</p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p> </p>
</td>
<td>
<p> </p>
</td>
</tr>
<tr>
<td>
<p>colonysize.csv</p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p> </p>
</td>
<td>
<p> </p>
</td>
</tr>
<tr>
<td>
<p>wfinfo.csv</p>
</td>
<td>
<p class="rtecenter"> </p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p> </p>
</td>
</tr>
<tr>
<td>
<p>wfstats.csv</p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p> </p>
</td>
</tr>
<tr>
<td>
<p>parameters.csv</p>
</td>
<td>
<p> </p>
</td>
<td>
<p class="rtecenter"> </p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
</tr>
<tr>
<td>
<p>spatial.csv</p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
<td>
<p class="rtecenter"> </p>
</td>
<td>
<p class="rtecenter">Yes</p>
</td>
</tr>
</tbody>
</table>
<p><strong>Model Functions</strong></p>
<p>Three functions are used to directly run the model and process the output; the actual calculations are performed by a number of additional functions, but these are not called directly by the user.</p>
<p>“<strong>vsdm.runmodel</strong>” runs the model for a single set of parameter values. The arguments are:</p>
<p> dat : spatial distribution of the species</p>
<p> species : species name</p>
<p> meta : meta information about SPAs and wind farms</p>
<p> pars.full : parameter values</p>
<p> pars.version : which version of the parameters to use (default is to use pars.version=0, which corresponds to none of the alternative versions being used)</p>
<p> ppop : which proportion of the population to use for simulation (default is to use ppop = 1, which corresponds to 100% of the population)</p>
<p> min.prey.adjust : ratio to use for adjusting minimum prey values</p>
<p> seedval.location : random seeds to use for simulating locations; set automatically if not specified</p>
<p> seedval.behaviour : random seed to use for simulation foraging behaviour; set automatically if not specified</p>
<p>“<strong>vsdm.sensitivity</strong>” runs the model for all parameter sets listed in the ‘parameters.csv’ file. The arguments are identical to those for “<strong>vsdm.runmodel</strong>” except that ‘pars.version’ is no longer an option (since the model is now run for all versions).</p>
<p>“<strong>getsummary.zones</strong>” summarizes the output from “<strong>vsdm.sensitivity</strong>” in a format that can be used to create a CSV file (spreadsheet). The sole argument is ‘out’, the output from running "<strong>vsdm.sensitivity</strong>".</p>
<p><strong>Example</strong></p>
<p>The following contains the R code used to run the analysis for kittiwake.</p>
<p>setwd("~/Work/Project/CEH/Displacement/SimplifiedModel/CurrentModel/")</p>
<p>source("Simplified-Displacement-Model-Version17.R")</p>
<p>pars.full <- (read.csv("Parameters/parameters-gps.csv"))[,3:9]</p>
<p>meta <- list(wf = read.csv("Meta/wfinfo.csv"), colony = read.csv("Meta/colonies.csv"), colonysize = read.csv("Meta/colonysize.csv"), wfstats = read.csv("Meta/wfstats.csv"))</p>
<p>levels(meta$colony$colony) <- c("ForthIslands", "Boddam", "FAR", "Fowlsheugh", "ForthIslands", "StAbbsHead", "TPL")</p>
<p>levels(meta$wfstats$SPA)[3] <- "ForthIslands"</p>
<p>## Species-specific part :</p>
<p>dat <- read.csv("/tmpshare/adam/projects/seabirds/Displacement/out-sixth/kittiwake.csv")</p>
<p>levels(dat$Site)[3] <- "ForthIslands"</p>
<p>out.kittiwake <- vsdm.sensitivity(dat, species = "Kittiwake", meta = meta, pars.full = pars.full, ppop = 1/3)</p>
<p> write.csv(getsummary.zones(out.kittiwake), file="Output/sensitivity-kittiwake.csv", quote=FALSE, row.names=FALSE)</p>
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xsd:dateTimedate_iso8601https://marine.gov.scot/information/displacement-model-foraging-seabirdsDrewa:5:{s:16:"ckeditor_default";s:1:"t";s:20:"ckeditor_show_toggle";s:1:"t";s:14:"ckeditor_width";s:4:"100%";s:13:"ckeditor_lang";s:2:"en";s:18:"ckeditor_auto_lang";s:1:"t";}9254610506613572publishedpublished21150608693511Displacement Model: Foraging Seabirds15060869359254610506613572publishedpublished21150608693511Displacement Model: Foraging Seabirds15060869359254610506613572publishedpublished21150608693511Displacement Model: Foraging Seabirds1506086935