Inquiry about Integrating WorldClim Dataset (v2.1) with NicheMapR

[曾城]

Hello everyone,

Recently, I have become aware of NicheMapR, a powerful tool for bioclimatic analysis.I am currently using the WorldClim dataset (Version 2.1) to conduct research on species distribution patterns. However, I am encountering difficulties in understanding the specific process of referencing or integrating the WorldClim dataset within the NicheMapR framework. I am writing to seek your guidance on the following questions:

1.Can the micro_global function be modified to call climate layers from other databases (e.g., WorldClim)?

2.What data preprocessing steps are recommended for WorldClim to meet NicheMapR's input requirements?

3.Are there technical documents/tutorials/case studies on NicheMapR integrating external databases?

Best regards,
Lin Qianjin

[David Klinges]

Hi Lin,

Welcome to the community! Mike Kearney, the lead developer of NicheMapR, can jump in with more details, but as a quick reply: most of the WorldClim products are bioclimat normals, meaning they represent conditions averaged across long periods of time. That's not exactly conducive to the fine timesteps that are usually integral to biophysical modeling, such as via NicheMapR.

Instead, NicheMapR is integrated with several other external climate databases. You can see this page for an overview. For micro_global(), check out this tutorial. The most comprehensive global climate source integrated with NicheMapR is ERA5, which is accessed via micro_era5() and another R package mcera5(). See this paper and the mcera5 vignette:

remotes::install_github("dklinges9/mcera5")
vignette("mcera5_vignette")




Hope that helps. Best,

Dave

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David Klinges, PhD

Assistant Professor, Rutgers University (incoming)

https://ecoclimateglobal.org/

Google Scholar Page

[NicheMapR]

Hi Lin and Dave,

I should put a function together for WorldClim because it now has all the necessary variables (now that it has wind speed, solar radiation and vapour pressure). As Dave points out, it would be for the typical day of each month given that it's monthly long-term climate averages but that's the same as what the micro_global function does and it is useful for some purposes. I'll make a 'micro_worldclim' function soon ...

All the best,

Mike

p.s. see here for how to connect the model to monthly gridded data