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Kujala et al (2018) Not all data are equal: Influence of data type and amount in spatial conservation prioritisation - Data

Version 2 2018-11-07, 05:42
Version 1 2018-08-28, 23:53
dataset
posted on 2018-11-07, 05:42 authored by HEINI KUJALA, JOSE LAHOZ-MONFORTJOSE LAHOZ-MONFORT, Jane Elith, Atte Moilanen
Data for Kujala et al (2018) Not all data are equal: Influence of data type and amount in spatial conservation prioritisation. Methods in Ecology and Evolution, 9(11): 2249-2261.
https://doi.org/10.1111/2041-210X.13084

Tables gives simulation results where 1) new species is added to a prioritisation done without ("_BD_n20_") or with costs ("_cost_n20_"); 2) landscape condition is accounted for but it affects onpy p-proportion of the species; and 3) condition layer is changed by x%. Table headings correspond to:

n_B = number of species used in the prioritisation
p = proportion of species affected by local condition
x = average change in condition values
cor = spatial correlation (Spearman's rank coefficient) between priorities and the added/changed layer values before addition/change
exp = expected average change in cell values after addition/change
obs_min/mean/max = minimum, mean and maximum of the observed average change in cell values (average across repeats)
rho_min/mean/max = minimum, mean and maximum correlation (Pearson's rho) between old and new priorities of cells
_S/_M/_L = small, medium or large, respectively, ranged values in the added/changed layer (for cost and condition analysis only)
_sd = standard deviation

Updates to this data:
7 Nov 2018 - Added explanations and full reference to the published article.
7 Nov 2018 - Data tables with condition analysis replaced. Original tables incorrectly showed results of the cost analysis.

Funding

Australian Research Centre Discovery Project grant DP160101003; Academy of Finland Centre of Excellence programme 2012–2017, grant 250444

History