Data and outputs from: Spatial assessment of recreational fishing displacement from marine protected areas
Data files
May 13, 2026 version files 50.13 MB
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01_main.R
9.70 KB
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02_cells_zonation.R
719 B
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03_combine_final.R
5.31 KB
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config.yaml
804 B
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data.zip
874.66 KB
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features_template.txt
165 B
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figures.zip
170 B
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output.zip
10.16 MB
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README.md
21.95 KB
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sc_bio.zip
806.24 KB
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sc_cells.zip
37.77 MB
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sc_recfish.zip
482.24 KB
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settings_template.z5
32 B
Abstract
The establishment of marine protected areas (MPAs) to achieve healthy and resilient ecosystems is a proven conservation strategy to generate a wide range of ecological and socio-economic benefits. However, the planning and design of MPAs must be well thought out to avoid unintended management consequences. Among the things that practitioners should consider is the potential for fishing effort displaced from MPAs to exacerbate fishing impacts outside of MPAs. Commercial fisheries are generally well studied when analysing and predicting fishing displacement, but recreational fisheries often receive less attention. In this study, we analyse the spatial relationship between recreational fishing effort (estimates of recreational fishing vessel density) and the predicted habitat suitability of the main target fish species for recreational fishers in the Hauraki Gulf in northern New Zealand. A spatial prioritisation software, Zonation, was used to identify areas likely to receive fishing effort displacement due to the establishment of 14 new MPAs that exclude all recreational fishing and almost all commercial fishing. A ‘displaced effort index’ is provided for each protected area, as well as for the entire area of study, to help identify broad areas that are likely to absorb displaced recreational fishing effort. The index can help inform effectiveness of marine protected areas and identify areas that should be the focus of assessments of localised depletion of fisheries resources due to displaced effort. While the analysis described here is based in the Hauraki Gulf, the methodology can be adapted to different areas and other fisheries.
Tablada, J., Bennion, M., Geange, S.W., Duffy, C.A., Stephenson, F., Hartill, B.W., and Hiddink, J.G. (2026). Spatial assessment of recreational fishing displacement from marine protected areas. Ecosphere. https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecs2.0892
Dataset DOI: 10.5061/dryad.qfttdz0xb
Description of the data and file structure
This data archive contains all the necessary data and code to run and analyse multiple Zonation prioritisation scenarios to assess displacement of recreational fishing due to establishment of marine protected areas in northeastern New Zealand.
Summary of data
Data and code in this repository are structured in folders:
- sc_recfish.zip: Zonation scenario files for the fishing displacement scenario.
- sc_bio.zip: Zonation scenario files for the target species scenario.
- data.zip: Folder containing all input data (see Data layers section for details) for the Zonation scenarios and the R analaysis.
- sc_cells.zip: Zonation scenario files for the 847 displaced cells scenarios.
- figures.zip: Folder with the plots generated by the R scripts.
- output.zip: Folder with all raster files generated by the R scripts (details above), including final results.
- 01_main.R, 02_cells_zonation.R, 03_combine_final: sequential R scripts to analyse Zonation outputs and generate results and plots.
Usage notes
The different data types included in this repository are listed below, along with brief descriptions for how to work with them.
.R: R language file is a plain-text script that contains executable code written in the R programming language, typically used for statistical analysis and data processing. It is interpreted by the R runtime environment to perform computations, generate visualizations, and run data workflows.
.tif: a raster image format commonly used to store geospatial data, where pixel values represent information such as elevation, temperature, or land cover. It supports high-quality, multi-band data and is widely used in GIS and remote sensing applications. It may be accompanied by associated files that store relevant metadata (.dbf, .cpg, .tfw, .aux, .xml).
.shp: a core component of the ESRI Shapefile format used to store vector-based geospatial data, such as points, lines, or polygons. It contains the geometric shape information for spatial features and is typically used alongside associated files that store attributes and indexing data (.cpg, .dbf, .prj, .sbn, .sbx, .xml, .shx).
.png: Portable Network Graphics format that stores lossless compressed image data, preserving high visual quality. It supports transparency and is widely used for web graphics, digital images, and visual outputs where exact pixel fidelity is important.
.z5: A .z5 file is a configuration or settings file used by Zonation software, a tool for spatial conservation planning. It typically stores structured data that defines analysis parameters, input datasets, and prioritization settings used by the program.
.cmd: plain-text script used by the Windows command processor (Command Prompt) to execute a sequence of commands. It contains batch instructions for automating system tasks such as file operations, program execution, and environment configuration.
.csv: A CSV (comma-separated values) file is a plain text file used to store tabular data, such as spreadsheets or databases, with each row representing a record and each value within a row separated by a comma. Can be opened with software such as LibreOffice Calc, OpenOffice Calc, Microsoft Excel or imported into R using the read.csv function.
Files and variables
File: 01_main.R
Description:
- Evaluates correlation between outputs from Zonation scenarios:
- Fishing scenario:
./sc_recfish/ - Target species scenario:
./sc_bio/
- Fishing scenario:
- Plots correlation Figure 4
./figures/correlation_boxplot_filtered.png - Calculates distance rasters for each of the boat ramps and writes them in the
./output/distance_ramps/folder. - Uses distance rasters to create masks for each of the 847 cells and writes them in the
./output/masked_cells/folder. - Creates a Zonation setup for each one of the 847 cells under the
./sc_cells/folder.
File: 02_cells_zonation.R
Description: Executes all 847 cell Zonation scenarios (created in previous step) in sequence.
File: 03_combine_final.R
Description:
- Reads all 847 Zonation prioritisation rasters (outputs from previous step), combines them (func=sum) and filters the top 847 cells. Then individual top 10% area-based rasters are created, which are then combined as the total index displacement raster file:
- Individual MPA displaced index:
./output/top10percent_{MPA_NAME}.tif - Total displaced index:
./output/displacement_total_area.tif
- Individual MPA displaced index:
- Generates the facets plot distance-displacement Figure 7 for each individual MPA
./figures/pointcloud_faceted.png
File: config.yaml
Description: config settings for the R scripts, where paths to relevant data, folders, and to the Zonation .exe file within the user's system are defined.
File: features_template.txt
Description: template for Zonation scenarios input features. This file is used when the Zonation setup for each one of the 847 cells under the ./sc_cells/ folder is generated (see 01_main.R).
File: settings_template.z5
Description: template for Zonation settings. This file is used when the Zonation setup for each one of the 847 cells under the ./sc_cells/ folder is generated (see 01_main.R).
File: sc_recfish.zip
Description: Zonation scenario files for the fishing displacement scenario. The output folder contains the results of the Zonation run, but you can re-run the scenario using the given features.txt and the settings.z5. High-level description of Zonation's input and outputs:
/sc_recfish
- /features.txt → list of input features for this scenario
- /settings.z5 → Zonation settings for this scenario
/output → where Zonation writes all of its outputs
- /gui → this folder is created by default by Zonation and is populated when post-processing of results is applied, which wasn't the case in our analysis.
- /analysis.txt → log of the scenario run
- /feature_curves.csv → data to inform the input features performance curves plot generated by Zonation
- /features_info.csv → summary of information regarding input features for this scenario
- /issues.txt → log error (empty)
- /merged_rankmap.tif → sub-area priority rank raster (masked to the area of analysis)
- /rank_map.tif → priority rank raster
- /stats.txt → summary of numeric information (scenario grid size, number of cells, etc.)
- /summary_curves.csv → data to inform the performance curves plot generated by Zonation
- /subregion_1 → Zonation results for sub-area of analysis, which in our case are the same as the ones presented here (./output folder)
See Zonation 5 for additional Zonation information and use details.
File: sc_bio.zip
Description: Zonation scenario files for the target species scenario. The output folder contains the results of the Zonation run, but you can re-run the scenario using the given features.txt and the settings.z5. High-level description of Zonation's input and outputs:
/sc_bio
- /features.txt → list of input features for this scenario
- /settings.z5 → Zonation settings for this scenario
- /output → where Zonation writes all of its outputs
- /gui → this folder is created by default by Zonation and is populated when post-processing of results is applied, which wasn't the case in our analysis
- /analysis.txt → log of the scenario run
- /feature_curves.csv → data to inform the input features performance curves plot generated by Zonation
- /features_info.csv → summary of information regarding input features for this scenario
- /issues.txt → log error (empty)
- /merged_rankmap.tif → sub-area priority rank raster (masked to the area of analysis)
- /rank_map.tif → priority rank raster
- /stats.txt → summary of numeric information (scenario grid size, number of cells, etc.)
- /summary_curves.csv → data to inform the performance curves plot generated by Zonation
- /subregion_1 → Zonation results for sub-area of analysis, which in our case are the same as those presented in the
./outputfolder
See Zonation 5 for additional Zonation information and use details.
File: data.zip
Description: Folder containing all input data (see Data layers section for details).
File: sc_cells.zip
Description: Zonation scenario files for the 847 displaced cells scenarios. Each cell scenario has its own folder with the respective input files and outputs from the Zonation run. See example of a single cell scenario below:
/2748
- /features.txt → list of input features for this scenario
- /settings.z5 → Zonation settings for this scenario
- /2748.cmd → Windows command script to run this cell's scenario (this is executed as part of the
02_cells_zonation.Rscript) - /output → where Zonation writes all of its outputs
- /gui → this folder is created by default by Zonation and is populated when post-processing of results is applied, which wasn't the case in our analysis
- /analysis.txt → log of the scenario run
- /feature_curves.csv → data to inform the input features performance curves plot generated by Zonation
- /features_info.csv → summary of information regarding input features for this scenario
- /issues.txt → log error (empty)
- /rankmap.tif → priority rank raster
- /stats.txt → summary of numeric information (scenario grid size, number of cells, etc.)
- /summary_curves.csv → data to inform the performance curves plot generated by Zonation
See Zonation 5 for additional Zonation information and use details.
File: figures.zip
Description: Folder where the plots generated by the R scripts are written to.
File: output.zip
Description: Folder with all raster (distance and masks) files generated by the R scripts (details above) to be used in the 847 displaced cells scenarios and final results.
/distance_ramps -> contains Euclidean distance raster files for each boat ramp/marina used in our analysis. These are used to calculate, for each cell scenario, the area of analysis based on the cell's distance to the three nearest boat ramps/marinas. Each file name follows the convention dist_grid_{BOAT_RAMP_ID}{BOAT_RAMP_NAME}.tif
/masked_cells -> contains 847 mask rasters, one for each cell scenario. Each cell sceario makes reference to each raster, in their respective settings.z5 file. Each file name follows the convention masked_cell_{CELL_ID}.tif
Data layers
All input data is located in the ./data/ folder:
| Folder | File | Description | CRS | Resolution | Units | Link |
|---|---|---|---|---|---|---|
| BoatRamps | SHP | Location of boat ramps and marinas | Albers Equal Area | meters (1.0) | https://www.seasketch.org/rtg/app | |
| Distance | EuclideanDistance.tif | Euclidean distance | Albers Equal Area | 1 km x 1 km | meters (1.0) | |
| HPAs | SHP | High Protection Area polygons | Albers Equal Area | meters (1.0) | https://doc-marine-data-deptconservation.hub.arcgis.com/datasets/4b0a74880f554ce1a8e1fa46a3bbd3ce_0/ | |
| MarineReserves | SHP | Marine reserves polygons | New Zealand Transverse Mercator NZGD2000 | meters (1.0) | https://doc-marine-data-deptconservation.hub.arcgis.com/datasets/0e74f9682502447c9a14d51340512361_0/ | |
| masks | mask_HG.tif | Mask raster indicating extent of Hauraki Gulf Marine Park | Albers Equal Area | 1 km x 1 km | Boolean 0 (false) 1 (true) | https://doc-marine-data-deptconservation.hub.arcgis.com/datasets/c6d428a2199046d2a39dc2208a2c921f_4/ |
| PhysicalHabitats | HG_PhysicalHabitats_1km.tif | Physical habitat classification for the Hauraki Gulf Marine Park | Albers Equal Area | 1 km x 1 km | Habitat type [1 - 44] | https://doc-marine-data-deptconservation.hub.arcgis.com/datasets/414aac5c49e14f36b7779ef1b79318c1_0/about |
| RecFishingDensity | RecFishVessKm2_HG.tif | Recreational fishing density (number of vessels per km2) | Albers Equal Area | 1 km x 1 km | meters (1.0) | https://data-mpi.opendata.arcgis.com/datasets/MPI::recreational-fishing-effort-aerial-survey/ |
| SDMs | KahawaiDem.tif | Habitat suitability index value for kahawai (demersal) | Albers Equal Area | 1 km x 1 km | HSI value [0 - 1] | https://zenodo.org/records/7083642 |
| SDMs | KahawaiReef.tif | Habitat suitability index value for kahawai (reef) | Albers Equal Area | 1 km x 1 km | HSI value [0 - 1] | https://zenodo.org/records/7083642 |
| SDMs | SnapperDem.tif | Habitat suitability index value for snapper (demersal) | Albers Equal Area | 1 km x 1 km | HSI value [0 - 1] | https://zenodo.org/records/7083642 |
| SDMs | SnapperReef.tif | Habitat suitability index value for snapper (reef) | Albers Equal Area | 1 km x 1 km | HSI value [0 - 1] | https://zenodo.org/records/7083642 |
Further data details
Cell values [1-15] and associated labels.
| Value | Label [vessels/km2] |
|---|---|
| 1 | 0 – 0.01 |
| 2 | 0.01 – 1 |
| 3 | 1.01 – 2 |
| 4 | 2.01 – 5 |
| 5 | 5.01 – 10 |
| 6 | 10.01 – 15 |
| 7 | 15.01 – 20 |
| 8 | 20.01 – 50 |
| 9 | 50.01 – 100 |
| 10 | 100.01 – 150 |
| 11 | 150.01 – 200 |
| 12 | 200.01 – 250 |
| 13 | 250.01 – 300 |
| 14 | 300.01 – 400 |
| 15 | 400.01 – 500 |
Cell values and associated habitats.
ID Habitat
1 Estuarine Shallow Sand
3 Very Sheltered Shallow Sand
4 Estuarine Intertidal Rocky Reef
5 Estuarine Intertidal Soft Sediment
6 Estuarine Shallow Mud
7 Estuarine Shallow Rocky Reef
8 High Current Deep Gravel
9 High Current Deep Mud
11 High Current Deep Sand
14 High Current Shallow Gravel
15 High Current Shallow Mud
16 High Current Shallow Rocky Reef
17 High Current Shallow Sand
18 Moderate Deep Gravel
19 Moderate Deep Mud
20 Moderate Deep Rocky Reef
21 Moderate Deep Sand
22 Moderate Mid-slope Mud
25 Moderate Shallow Rocky Reef
26 Moderate Shallow Sand
27 Moderate Upper Slope Mud
28 Moderate Upper Slope Sand
29 Sheltered Deep Gravel
30 Sheltered Deep Mud
32 Sheltered Deep Sand
33 Sheltered Intertidal Rocky Reef
34 Sheltered Intertidal Soft Sediment
35 Sheltered Shallow Gravel
36 Sheltered Shallow Mud
37 Sheltered Shallow Rocky Reef
38 Sheltered Shallow Sand
39 Very Sheltered Deep Gravel
40 Very Sheltered Deep Mud
42 Very Sheltered Deep Sand
43 Very Sheltered Intertidal Rocky Reef
44 Very Sheltered Intertidal Soft Sediment
45 Very Sheltered Shallow Gravel
46 Very Sheltered Shallow Mud
47 Very Sheltered Shallow Rocky Reef
Code/software
Zonation v5 was used to run all scenarios https://zonationteam.github.io/Zonation5/
All R scripts were run in:
platform x86_64-w64-mingw32
arch x86_64
os mingw32
crt ucrt
system x86_64, mingw32
status
major 4
minor 4.1
year 2024
month 06
day 14
svn rev 86737
language R
version.string R version 4.4.1 (2024-06-14 ucrt)
nickname Race for Your Life
Access information
External data sources
Citations for formally published data:
Species distributions models
Stephenson, F., Brough, T., Lohrer, D., Leduc, D., Geange, S., Anderson, O., Bowden, D., Clark, M. R., Davey, N., Pardo, E., Gordon, D. P., Finucci, B., Kelly, M., Macpherson, D., McCartain, L., Mills, S., Neill, K., Nelson, W., Peart, R., Pinkerton, M. H., Read, G. B., Robertson, J., Rowden, A., Schnabel, K., Stewart, A., Struthers, C., Tait, L., Tracey, D., Weston, S., and Lundquist, C.: An atlas of seabed biodiversity for Aotearoa New Zealand, Earth Syst. Sci. Data, 15, 3931–3939, https://doi.org/10.5194/essd-15-3931-2023, 2023.
Vessel density layer
Hartill, B., Rush, N., Armiger, H., and Bian, R. 2019. "Aerial-access recreational harvest estimates for snapper, kahawai, red gurnard, tarakihi and trevally in FMA 1 in 2017–18." New Zealand Fisheries Assessment Report, 23, 39.
Physical habitats layer
Jackson, S. E., and C. J. Lundquist. 2016. "Limitations of biophysical habitats as biodiversity surrogates in the Hauraki Gulf Marine Park." Pacific Conservation Biology 22:159-172.
