Giter Site home page Giter Site logo

rle_indices's Introduction

Ecosystem indices to support global biodiversity conservation

Example code for Rowland JA, Bland LM, Keith DA, Juffe‐Bignoli D, Burgman MA, Etter A, Ferrer‐Paris JR, Miller RM, Skowno AL, Nicholson E. 2020. Ecosystem indices to support global biodiversity conservation. Conservation Letters 13:311. DOI: http://dx.doi.org/10.1111/conl.12680

The three scripts provided here include methods to calculate the three ecosystem indices presented in Rowland et al. (2020). Each script provides the code used to calculate each index and provides examples of the index output using the sample data as .csv files. The example data are from the continental assessment of the 136 temperate and tropical forests across 51 countries/territories in the Caribbean and Americas (Ferrer-Paris et al., 2018). The csv files are provided to demonstrate the structure of data required to calculate the indices.

Ferrer-Paris, J. R., Zager, I., Keith, D. A., Oliveira-Miranda, M. A., Rodríguez, J. P., Josse, C., … Barrow, E. (2018). An ecosystem risk assessment of temperate and tropical forests of the Americas with an outlook on future conservation strategies. Conservation Letters, 12. https://doi.org/10.1111/conl.12623

Red List Index of Ecosystems

Index overview

The Red List Index of ecosystems (RLIE) measures trends in ecosystem collapse risk. It uses the risk categories defined based on IUCN Red List of Ecosystems risk assessments. The index complements the Red List Index of species survival, providing comparable information about ecosystems risk. It is calculated for the overall risk category assigned to each ecosystem and separately for each criterion.

Ecosystem Area Index

Index overview

The Ecosystem Area Index (EAI) measures trends measures trends in changes in ecosystem area towards ecosystem collapse. The EAI is the geometric mean of the proportion of ecosystem area remaining over a given timeframe relative to the initial area and an ecosystem-specific collapse threshold. It uses data on ecosystem area and aea-based collapse threshold as defined based on IUCN Red List of Ecosystems risk assessments.

Ecosystem Health Index

Index overview

The Ecosystem Health Index (EHI) measures temporal changes in environmental conditions and biotic processes/interactions (hereafter collectively, ecological processes). The EHI uses relative severity of change in ecosystem-specific ecological variables and extent of the ecosystem affected to quantify transitions towards or away from ecosystem collapse. The index represents the geometric mean of the relative value of decline. It uses data defined in IUCN Red List of Ecosystems risk assessments.

rle_indices's People

Contributors

calvinkflee avatar

Stargazers

GlennML avatar Savvas Paragkamian avatar Uriel A. Torres Zevallos avatar

Watchers

James Cloos avatar John Wilshire avatar José R. Ferrer Paris avatar  avatar  avatar Nick Murray avatar Aurélien Boyé avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.