KISSMig

... a „Keep It Simple Species Migration model“ for R

KISSMig is a simple, grid-based model designed to simulate species distribution dynamics in R (Nobis & Normand 2014). Starting from an initial distribution, KISSMig generates subsequent species distributions, taking into account environmental suitability and the species’ migration ability. The environment can either remain stable or change over time. The model’s name refers to “Keep-It-Simple-Species-Migration-model” and the KISS principle, emphasizing simplicity and fast execution.

A central goal of macroecology and biogeography is to gain a deeper understanding of species distributions and their dynamics. However, these dynamics are often not explicitly considered in the analyses of past, present, or future species distributions. This is particularly true when only habitat suitability models are used (a.k.a. environmental niche models, or somewhat misleadingly species distribution models). On the other hand, models that explicitly take distribution dynamics into account are often complex and computationally demanding. KISSMig offers a simple approach to dynamic species distribution modeling, and can be used for different modeling tasks: For reconstructing past species distributions (Nobis & Normand 2014, Sen et al. 2025), for reducing overprediction of current species distributions by “filling in” suitable areas from known occurrences, or for analyzing the migration constraints of species under future climate change (Subba et al. 2018, Liao et al. 2020).

KISSMig is available as an R package on CRAN. A simple kissmig call requires only three parameters: (1) a map of the initial geographic distribution of the species, (2) one or more suitability layers from a habitat suitability model, and (3) the number of simulated migration steps corresponding to the species' migration ability. KISSMig does not require prior knowledge of the species-specific migration ability, as this can be optimized “on-the-fly” during an analysis (Nobis & Normand 2014, Sen et al. 2025). The R script kissmig_examples.R provides first steps how to run simple kissmig calls. 

• How to use KISSMig in R (kissmig_examples.R)

It is recommended to initially use KISSMig with binary suitability maps. Information on how to scale quantitative suitability can be found here: 

• Scaling suitability for KISSMig (kissmig_suitability.pdf) - update for v2.0 will follow soon