Git Product home page Git Product logo

nis_distinctiveness's Introduction

NIS_distinctiveness

This repository contains all the compiled data, code and further generated data from the work "A trait-based approach to assess niche overlap and functional distinctiveness between non-indigenous and native species" authored by Antoni Vivó-Pons, Mats Blomqvist, Anna Törnroos and Martin Lindegren.

IMPORTANT: ALL the plots and figure panels shown in the manuscript were post-processed in Adobe Illustrator, therefore the "raw" versions of the plots obtained with the following code might have different variable names or not be gathered in the same way as they appear in the manuscript. Additionally, the NIS illustrations shown within some figures were also created using Adobe Illustrator. In any case, the provided code allows for obtaining identical, but raw versions of all the figures included in the manuscript.

Data description

The folder Raw_data contains the original data files from which all the other databases included in the Data folder are derived.

Raw_data

  • env_data.txt; contains all the environmental data extracted from the ice-ocean NEMO nordic model.
  • sp_status.txt; accounts for the name, phylum and origin (native or NIS) from all the included taxa.
  • sp_traits_raw.txt; trait information for all species.
  • species_AFDW_2005_2020.txt; species abundance measures (n individuals, wet weight, AFDW) and details for all the specific sampling events
  • species_site_AFDW_2005.txt; site x species biomass (AFDW) matrix

Data

  • Di_metrics_station.txt; several metrics obtained at local scale, in each sampling event, including NIS local distinctiveness, species richness and Shannon index, among others.
  • Trait_modalities; list with all the trait and corresponding modalities.
  • dist_matrix_ovrll.txt; overall pairwise matrix of functional distances between species.
  • sp_traits.txt; cleaned species traits used in the analysis.
  • spe_index.txt; distinctiveness values for all species in the regional pool.
  • traits.effects.txt; effect of each trait on regional distinctiveness for each species.

Code description

Libraries. List of required libraries.

Functions. List of needed functions.

01_Descriptive_figures. This script contains the code related to the descriptive figures of the data used in the study.

02_Distinctiveness_regional (Step I & II). This script corresponds to the 1st and 2nd steps from the proposed framework, related to the computation of functional distinctiveness of NIS and natives at a regional scale (regional species pool).

03_Distinctiveness_local (Step III). This script corresponds to the 3rd step from the proposed framework, related to the computation of functional distinctiveness of NIS together with other community metrics at a local scale (local species pools).

04_Statistical_analysis (Step III). This script contains all the code related with the multi- and single modeling approaches included in the study to detect potential drivers of NIS distinctiveness at a local scale.

Env_data_extraction. Example of extracting environmental data from several .NC files, downloaded from the Copernicus Marine Service.

nis_distinctiveness's People

Contributors

tonivp avatar

Stargazers

 avatar  avatar

Watchers

 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.