Spatial Prioritization of Marine Protected Areas for sharks and rays in the Mozambique Channel using prioritizr
This repo uses the prioritizr R package to build and solve conservation planning problems. Similar to the spatial prioritization tool Marxan, the underlying objective of prioritizr is to design reserves (or areas) that achieve a conservation goal in a spatially efficient way.
More information on the prioritizr R package can be found here: https://prioritizr.net/
The prioritizr R package can be used to build reproducible spatial prioritization models in R and is a great spatial planning tool that can help inform decisions on how and where to focus conservation efforts given limited resources.
It can be used to identify, map, and prioritize sites or areas based on specific goals, targets and costs which can be custom-tailored to specific needs of different conservation planning exercises. For example, in prioritizr, the problem objective defines the overall goal of the conservation plan and this can be done a number of ways including using a minimum set objective which minimizes the cost of a reserve network, while ensuring all targets are met; maximum features objective, which fulfills as many targets as possible within a specific budget; maximum phylogenetic diversity objective which maximizes phylogenetic diversity of features within a specific budget; and more.
This repo looks prioritizing areas to protect for 27 shark and ray species in the Mozambique Channel based on their critical habitats, distribution ranges and fishing pressure threats.
You'll need 6 inputs to run your prioritizr model, they include:
- Planning Unit: The planning unit layer are spatial sub-units of the entire planning area
- Conservation Features: Features you'll be setting your targets for like, species distribution ranges, critical habitat, etc.
- Targets: The percent of the conservation features you aim to prioritize
- Constraints: Any sort of data or features we would want to lock in or lock out of the designs.
- Connectivity: Determine the fragmentation of your reserve design by including a boundary length modifier/boundary penalty
- Costs: The cost layer specifies the cost of including each planning unit in the reserve system.
To run prioritizr you will need to use an optimization tool or algorithm solver. Gurobi is a widely used option and is available for free use under an academic license. Follow the tutorial on how to obtain a license and how to install the optimizer onto your MAC or PC. You won't be able to run prioritizr without an optimization tool installed on your machine. More information can be found here: https://www.gurobi.com/
Below is a step by step guide to obtaining a free Gurobi academic license & installation instructions:
Step 1. Register on Gurobi website as Acedemic user: https://pages.gurobi.com/registration
Step 2. Once logged in, navigate to https://www.gurobi.com/free-trial/
Step 3. Click 'Academic Users: Request a Free Academic License'
Step 4. Click 'Download Gurobi Optimizer' page
Step 5. Download and install 'Gurobi Optimizer' - be sure to download the appropriate version for your computer (NOTE if you have a mac and R 4.0.3 - download the Gurobi for '64-bit macOS Universal2 – Experimental*')
Step 5. Navigate back to 'Download Gurobi Optimizer Page (https://www.gurobi.com/downloads/) and in the section Request a License, click 'Academic License & follow installation instructions
Step 6. Check out the Quick Start guide for specifics of how to install the Gurobi package in R (the quick start guide can be found wherever you installed Gurobi locally)
-- for example, if you have a Mac and you downloaded the Gurobi version '64-bit macOS Universal2 – Experimental*'you will run something like this:
install.packages('/Library/gurobi912/macos_universal2/R/gurobi_9.1-2_R_4.0.3.tgz', repos=NULL)
** NOTE - Depending on your local R environment you might need to install the R package slam. To do this, you should issue the following command within R:
install.packages('slam')
Here are some packages you may need to run a spatial prioritization:
library(raster) - to rasterize shapefiles library(tidyverse) library(sf) - for special features (adding geometry) library(here) - file organization library(fasterize) - to format rasters with existing rasters CRS and extents library(stringr) library(janitor) - to update dates library(prioritizr) - to run prioritizr library(rgdal) - library(gurobi) - to run spatial optimizer Gurobi