| Title: | Identifying Conservation Prioritization Methods Based on Data Availability |
| Version: | 1.0.4 |
| Description: | Helping biologists to choose the most suitable approach to link their research to conservation. After answering few questions on the data available, geographic and taxonomic scope, 'conserveR' ranks existing methods for conservation prioritization and systematic conservation planning by suitability. The methods data base of 'conserveR' contains 133 methods for conservation prioritization based on a systematic review of > 12,000 scientific publications from the fields of spatial conservation prioritization, systematic conservation planning, biogeography and ecology. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.1.1 |
| Language: | en-US |
| Imports: | cowplot, GGally, ggplot2, ggrepel, magrittr, network, rlang, scales, sna, utils |
| URL: | https://github.com/azizka/conserveR |
| BugReports: | https://github.com/azizka/conserveR/issues |
| Depends: | R (≥ 3.5.0) |
| NeedsCompilation: | no |
| Packaged: | 2021-07-30 07:44:06 UTC; az64mycy |
| Author: | Alexander Zizka 
[aut, cre] |
| Maintainer: | Alexander Zizka <alexander.zizka@idiv.de> |
| Repository: | CRAN |
| Date/Publication: | 2021-08-02 09:10:06 UTC |
connectivity_network
A bipartite network of methods included in the conserveR package linked by shared cited references.
Used for visualization in map_selection
Description
connectivity_network
A bipartite network of methods included in the conserveR package linked by shared cited references.
Used for visualization in map_selection
Usage
connectivity_network
Format
An object of class network of length 5.
edge
An example dataset of the output of find_method. Conservation prioritization methods prioritized
by fit to an example set of data requirements.
Description
edge
An example dataset of the output of find_method. Conservation prioritization methods prioritized
by fit to an example set of data requirements.
Usage
edge
Format
An object of class data.frame with 134 rows and 9 columns.
Identify Most Suitable Methods for Conservation Prioritization
Description
Identifies suitable methods for conservation prioritization based on a user dialogue on conservation targets and data availability.
Usage
find_method(ranking = "both", weights = NULL)
Arguments
ranking |
character string. The methods used for ranking the methods. See details. One of "both", "strict", "inclusive". Default = "both". |
weights |
named list. Provide numeric values to weight questions differently. See details. |
Details
Based on the ranking argument, the conservation prioritization methods in the database are
ranked according to the user-provided information. If ranking = "strict" methods receive
one point for each full agreement with user reply (yes and no), if ranking = "inclusive",
methods get one point when they include a feature confirmed by the user (but non for not including it).
This means that ranking = "inclusive" will likely return more general methods
that can include many different types of data and perspectives. If ranking = "both",
methods are first ranked as in strict and then equal ranks split by the inclusive ranking.
The weight argument allows to change the weighting of individual questions relative to the others.
The names of the list follow names(traits), from “scale” (for question 1) to
“includes_simulation” (for question 17). The weights may include any numbers of questions.
See examples
Value
a data.frame containing potentially suitable spatial conservation prioritization methods order by goodness of fit according to the user-selected algorithm (best fit on top). Furthermore prints the three most suitable methods to screen.
Examples
## Not run:
find_method()
#double weight to question 3 and 15
find_method(weights = list(phylogeny = 2, vulnerability = 2))
## End(Not run)
Literature
Description
Literature references for all conservation prioritization methods listed in traits, in bib2format.
Usage
literature
Format
An object of class tbl_df (inherits from tbl, data.frame) with 134 rows and 43 columns.
Map Selected Methods to Context
Description
Maps methods selected with find_method to the trait space
and/or citation network of methods included in conserveR,
to identify further similar methods.
Usage
map_selection(x, num = 3, type = "both")
Arguments
x |
data.frame. As produced by |
num |
numerical. The number of top ranking methods to highlight. |
type |
character. The type of plot, either “mca” for the results of a multiple correspondence analyses of the trait space, “citation” for the citation network, or “both” for both. |
Value
a plot highlighting the position of the best fitting methods in the context of all conservation prioritization methods included in the package. Includes two subplots
a multidimensional trait space resulting from a multiple correspondence analysis,
a citation network linking different methods by shred scientific publications.
Examples
data(edge)
map_selection(edge)
mca_results
Description
Results of a multiple correspondence analysis of all methods included in the conserveR package based on the traits data set.
Used for visualization in map_selection.
Usage
mca_results
Format
An object of class tbl_df (inherits from tbl, data.frame) with 134 rows and 7 columns.
Traits
Description
The dataset of conservation prioritization methods for relevant for macro-evolution and macro-ecology including information on data needs, "method traits" and met-data
Usage
traits
Format
A data frame with thirty-one variables:
- author
The last name of the first author.
- year
The publication year.
- acronym
The acronym of the method as suggested by the authors, or a custom one if there was none available
- method_name
The full name of the method as suggested by the authors.
- scale
- scalability
A qualitative assessment how scalable the methods are to large-scale analyses with hundreds of species or global extent.
- implementation_standard
How is the method implemented/how can it be used by people, i.e. a software or similar that anyone that would like to use the method could use. "none" if no implementation exists.
- target
The target of the method. Either "species" or "area".
- scope_terrestrial
Can the method be applied to terrestrial species/systems? 1 = yes, 0 = no.
- scope_marine
Can the method be applied to marine species/systems? 1 = yes, 0 = no.
- scope_limnic
Can the method be applied to limnic species/systems? 1 = yes, 0 = no
- phylogeny
Does the method include evolutionary aspects (i.e. does it at any point use a phylogeny as input) to prioritize conservation efforts? 1 = yes, 0 = no.
- distribution
Does the method include distribution aspects of species (i.e. any type of distribution information as input, e.g. species ranges, grid-cell occupancy or occurrence records) to prioritize conservation? 1 = yes, 0 = no.
- functional
Does the method include functional aspects of species (i.e. functional traits as input data) to prioritize conservation? 1 = yes, 0 = no.
- rarity
Does the method include species' rarity or commonness (i.e. species abundances as input data) to prioritize conservation? 1 = yes, 0 = no.
- pop_dynamics
Does the method include changes in species' population density through time? 1 = yes, 0 = no.
- genetics
Does the method include genetic aspects (i.e. sequence data as input)? For example genetic diversity. 1 = yes, 0 = no.
- ecosystem_services
Does the method include the importance of species or areas for ecosystem services to prioritize conservation? 1 = yes, 0 = no.
- socio_economic
Does the method include socio-economic values of species or areas to prioritize conservation effort? 1 = yes, 0 = no.
- landscape_connectivity
Does the method include landscape connectivity to prioritize conservation effort? 1 = yes, 0 = no.
- land_use
Does the method include land use factors (i.e. land use data, for instance modeled or remotely sensed) for conservation prioritization? 1 = yes, 0 = no.
- protected_area
Does the method include protected areas in some way to prioritize conservation effort? 1 = yes, 0 = no.
- extinction_risk
Does the method include species extinction risk in any way (i.e. the International Union for the Conservation of Nature assessment categories as input data) for conservation prioritization? 1 = yes, 0 = no.
- environment
Does the method include environmental variables (e.g., modeled precipitation, species niche or worldclim data as input data)?
- vulnerability
Does the method include assessments of the vulnerability of species or areas to specific threats, for instance pollution, hunting or logging? 1 = yes, 0 = no
- climate_change
Does the method include climate change as explicit factor for conservation prioritization?
- includes_simulation
Does the method include the possibility to conduct simulations?
- free_text_description
- DOI/link
The digital object identifier or link to a scientific publication.
- ID
The ID to link with the
literature- example_taxon_standard
On which taxon was the method developed/tested?
- example_area_standard
In which area was the method developed/tested?