-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Showing
1 changed file
with
2 additions
and
2 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
|
@@ -3,9 +3,9 @@ | |
## Overview | ||
|
||
This repository houses scripts with data and analyses for: | ||
> Crawford C.L.[\*1], Estes L.D., Searchinger T.D., and Wilcove, D.S. 2021. Consequences of under-explored variation in biodiversity indices used for land-use prioritization. *Ecological Applications.* | ||
> Crawford C.L.[^\*], Estes L.D., Searchinger T.D., and Wilcove, D.S. 2021. Consequences of under-explored variation in biodiversity indices used for land-use prioritization. *Ecological Applications.* | ||
\*Corresponding Author, @chriscra, [email protected], Robertson Hall, Princeton University, Princeton, NJ | ||
[^\*]: Corresponding Author, @chriscra, [email protected], Robertson Hall, Princeton University, Princeton, NJ | ||
|
||
We explore how variation in the design of biodiversity indices affects the outcome of land-use prioritization. We use the [`agroEcoTradeoff`](https://github.com/PrincetonUniversity/agroEcoTradeoff) land-use prioritization model (Estes and Spiegel 2016), a trade-off model designed to identify areas for agricultural expansion that meet a given production target at the least environmental cost, and apply the model to a case study in Zambia. The [`agroEcoTradeoff`](https://github.com/PrincetonUniversity/agroEcoTradeoff) model allows users to minimize four constraints -- 1) biodiversity loss, 2) total agricultural area (maximizing yields), 3) carbon loss, and 4) transportation costs. Our analysis focuses on how biodiversity loss is modeled: specifically, we assess agreement between the least biodiverse areas in Zambia as identified by biodiversity indices that vary in their construction. We explore results for a wide range of criteria and methods that biologists and land-use planners have used, including: published composite indices, vertebrate taxonomic groups, metrics of species richness, methods for combining layers, and spatial resolutions. | ||
|
||
|