![]() ![]() And then we will load the ggplot2, tibble, and tidyr R packages to help with data for visualizations and wrangling. To start off, we will initialize the random number generator to ensure reproducibility. For more background information on project prioritization, please refer to Carwardine et al. This is important because we can’t find a cost-effective solution if we don’t know how much each project improves a species’ chance at persistence. The conservation projects should also include a “baseline project” that represents a “do nothing scenario” which has a 100% chance of succeeding and is associated with an action that costs nothing to implement. Each conservation project should be associated with (i) a probability of succeeding if it is implemented (also termed “feasibility”), (ii) information about which management actions are associated with it, and (iii) an estimate of how likely each conservation feature affected by the project is to persist into the future if the project is implemented (often derived using expert elicitation). Additionally, some conservation projects can be combinations of other projects (e.g. a “pest and habitat project”). ![]() Typically, management actions are grouped into conservation projects based on spatial (e.g. management actions that pertain to the same area), taxonomic (e.g. management actions that pertain to the same pest species or threatened species), or thematic criteria (e.g. management actions that pertain to pest eradication are grouped into a “pest project”, and actions that pertain to habitat restoration are grouped into a “habitat project”). To guide the prioritization, the management actions are grouped into conservation projects (also termed “strategies”). Each action should pertain to a specific location (e.g. a national park) or area (e.g. an entire country), and should be associated with a cost estimate. Management actions are acts that can be undertaken to enhance biodiversity (e.g. planting native species, reintroducing native species, trapping pest species). These biodiversity features can (and ideally should) include non-threatened species, but should not include threatening processes that we wish to eradicate (e.g. populations of invasive species). To develop a project prioritization, this package requires data for (i) conservation projects, (ii) management actions data, and (iii) biodiversity features.īriefly, biodiversity features are the biological entities that we wish would persist into the future (e.g. threatened populations, native species, eco-systems). 2014) and priority threat management problems (Carwardine et al. It can generate solutions for species-based project prioritization problems (Joseph et al. This package is a general purpose project prioritization decision support tool. Here we will provide a short tutorial showing how the oppr R package can be used to prioritize funding for conservation projects. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |