@article{fdi:010064716,
  title = {{M}apping diversity indices : not a trivial issue},
  author = {{G}ranger, {V}. and {B}ez, {N}icolas and {F}romentin, {J}. {M}. and {M}eynard, {C}. and {J}adaud, {A}. and {M}erigot, {B}.},
  editor = {},
  language = {{ENG}},
  abstract = {{M}apping diversity indices, that is estimating values in all locations of a given area from some sampled locations, is central to numerous research and applied fields in ecology. {T}wo approaches are used to map diversity indices without including abiotic or biotic variables: (i) the indirect approach, which consists in estimating each individual species distribution over the area, then stacking the distributions of all species to estimate and map a posteriori the diversity index, (ii) the direct approach, which relies on computing a diversity index in each sampled locations and then to interpolate these values to all locations of the studied area for mapping. {F}or both approaches, we document drawbacks from theoretical and practical viewpoints and argue about the need for adequate interpolation methods. {F}irst, we point out that the indirect approach is problematic because of the high proportion of rare species in natural communities. {T}his leads to zero-inflated distributions, which cannot be interpolated using standard statistical approaches. {S}econdly, the direct approach is inaccurate because diversity indices are not spatially additive, that is the diversity of a studied area (e.g. region) is not the sum of the local diversities. {T}herefore, the arithmetic variance and some of its derivatives, such as the variogram, are not appropriate to ecologically measure variation in diversity indices. {F}or the direct approach, we propose to consider the -diversity, which quantifies diversity variations between locations, by the mean of a -gram within the interpolation procedure. {W}e applied this method, as well as the traditional interpolation methods for comparison purposes on different faunistic and floristic data sets collected from scientific surveys. {W}e considered two common diversity indices, the species richness and the {R}ao's quadratic entropy, knowing that the above issues are true for complementary species diversity indices as well as those dealing with other biodiversity levels such as genetic diversity. {W}e conclude that none of the approaches provided an accurate mapping of diversity indices and that further methodological developments are still needed. {W}e finally discuss lines of research that may resolve this key issue, dealing with conditional simulations and models taking into account biotic and abiotic explanatory variables.},
  keywords = {interpolation methods ; map ; quadratic entropy ; spatial statistics ; species diversity ; species richness ; beta-diversity},
  booktitle = {},
  journal = {{M}ethods in {E}cology and {E}volution},
  volume = {6},
  numero = {6},
  pages = {688--696},
  ISSN = {2041-210{X}},
  year = {2015},
  DOI = {10.1111/2041-210x.12357},
  URL = {https://www.documentation.ird.fr/hor/fdi:010064716},
}