Using centroids of spatial units in ecological niche modelling: effects on model performance in the context of environmental data grain size

Yanchao Cheng, N.B Tjaden, Anja Jaeschke, Stephanie Margarete Thomas, Carl Beierkuhnlein

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Abstract

Aim:
Ecological niche models (ENMs) typically require point locations of species’ occurrence as input data. Where exact locations are not available, geographical centroids of the respective administrational spatial units (ASUs) are often used as a substitute. We investigated how the use of ASU centroids in ENMs affects model performance, what role the size of ASUs plays, and what effects different grain sizes of explanatory variables have.

Location: Europe.
Major taxa studied: Virtual species.

Methods:
We set up a two-factorial study design with artificial ASUs of three different sizes and environmental data of four commonly used grain sizes, repeated over three study regions. To control other factors that may affect ENM performance, we created a virtual species with a known response to environmental variables, precise and even sampling and a known spatial distribution. We ran a series of Maxent models for the virtual species based on centroids and precise occurrence locations under varying ASU and grain sizes.

Results:
The use of ASU centroids introduces a value frequency mismatch of the explanatory variables between centroids and true occurrence locations, and it has a negative effect on ENM performance. Value frequency mismatch, negative effect on ENM performance and over-prediction of the species’ range all increase with ASU size. The effect of grain size of environmental data, on the contrary, was small in comparison.

Main conclusions:
ENMs built upon ASU centroids can suffer considerably from the introduced error. For ASUs that are sufficiently small or show low spatial heterogeneity of explanatory variables, ASU centroids can still be a viable and convenient surrogate for precise occurrence locations. When possible, however, central tendency values (median, mean) that represent the whole ASU rather than just a single point location need to be considered.
Original languageEnglish
Pages (from-to)611-621
Number of pages11
JournalGlobal ecology and biogeography
Volume30
Issue number3
Early online date6 Jan 2021
DOIs
Publication statusPublished - Mar 2021
Externally publishedYes

Keywords

  • administrative spatial unit
  • centroid
  • county
  • ecological niche models
  • grain size
  • MaxEnt
  • Spatial heterogeneity
  • species distribution model
  • virtual species
  • ITC-CV

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