Thread by @Martin_Ecology

New paper for ‘ibis.iSDM’ now published in Ecological Informatics. Here I present a new R-package that allows the integration of different datatypes in SDMs. But it can do much more than that... #sdm #biodiversity #conservation
doi.org/10.1016/j.ecoi…
👇(1/8)

So one might ask why another R-package for correlative SDMs, and I generally agree. The specific role of the package for me and our group is to a) support all types of integration originally highlighted by Fletcher et al. and more (doi.org/10.1002/ecy.27…, @FletcherEcology) (2/8)

..., b) propose a modelling framework founded in Poisson Process Models and support Bayesian SDMs, c) enable easy construction of scenarios and projections and d) have a modular coding framework that can be easily updated with further functionalities (3/8)

The package follows a tidyverse and object based design. Meaning, that each model is contained in its own object, storing functions and data alike that can be modified or passed on to other functions or packages. The pseudo-code below shows how convenient this design can be (4/8)

SDMs can be parametrized in many ways. A common issue is extrapolation in projections, owing to a lack of model constraints or unquantified/latent variables. Example below highlights how projections can differ if we combine, integrate and constrain with other information (5/8).

Besides supporting a range of different engines (frequentist, Bayesian, ML, …) the package also allows the convenient addition of spatial latent effects in various forms, built-in “scenario” support and much more related to how models can be summarized or visualized (6/8).

Immediate development plans: Complete the integration with #stan and migrate to terra, endure the pain of a CRAN release, temporal-explicit projections and inferences, and also adding further mechanistic sub-modules to support population abundance / demographic simulations (7/8).

The package for sure won't be something for every user. But for more information and usage guidelines check out the articles and FAQ on the github page ( iiasa.github.io/ibis.iSDM/ ) and test out the package. Bug reports welcome and feature requests to some extent as well 😁 (8/8).