Miscellaneous methods and utilities for spatial ecology analysis, written by current and former members and collaborators of the ecospat group.
'ecospat' offers the possibility to perform Pre-modelling Analysis, such as Spatial autocorrelation analysis, MESS (Multivariate Environmental Similarity Surfaces) analyses, Phylogenetic diversity Measures, Biotic Interactions. It also provides functions to complement biomod2 in preparing the data, calibrating and evaluating (e.g. boyce index) and projecting the models. Complementary analysis based on model predictions (e.g. co- occurrences analyses) are also provided.
In addition, the ecospat package includes Niche Quantification and Overlap functions that were used in Broennimann et al. 2012 and Petitpierre et al. 2012 to quantify climatic niche shifts between the native and invaded ranges of invasive species.
Examples of how to use the functions:
Code-ecospat.pdf (657 Ko)
MigClim is an R package which allows simulating plant dispersal under climate change and landscape fragmentation scenarios. MigClim allows implementing various parameters, such as dispersal distance, increase in reproductive potential over time, landscape fragmentation or long-distance dispersal.
Engler R. and Guisan A., 2009. MIGCLIM: Predicting plant distribution and dispersal in a changing climate. Diversity and Distribution, 15 (4), 590-601.
Engler R., Randin C.F., Vittoz P., Czáka T., Beniston M., Zimmermann N.E., Guisan A., 2009. Predicting future distributions of mountain plants under climate change: does dispersal capacity matter? Ecography, 32 (1), 34-45.
Engler R., Hordijk W., Guisan A., 2012. The MIGCLIM R package – seamless integration of dispersal constraints into projections of species distribution models. Ecography, 35 (10), 872–878.
...and don't miss out the presentation video of Migclim featuring Robin Engler at the Global Online Seminar in Biodiversity Informatics help by A. Townsend Peterson at the University of Kansas: Youtube link
The R package 'ecospat' R now includes the functions to perform measures of niche overlap and niche equivalency/similarity tests.
Create a folder with a R shortcut. Use this folder as workspace by setting the path in the proprieties of the shortcut (right click). In this folder also put your datasets of occurences data (delimited text file with column names x,y) and datesets of points representing the study areas with environmental values (column names should be x,y,X1,X2,...,Xn).
The user scripts allow setting the analyses for the calculations with an example data. Use user_script_2sp_2A.R if you want to compare niches of 2 species in different areas (e.g. invasive species). Use user_script_Nsp_1A.R if you want to compare niches of n species in the same area.
Please note that the niche equivalency and similarity tests compare observed overlap values to simulated ones (i.e. random niches). So due to the non-parametric nature of the test, the p.value corresponds to the quantile of the observed value in the distribution of simulated values, and if the observed overlap is always outside of the simulated distribution the p.value will always be the same, e.g. one sided test with 100 repetitions:
p.values= min((sum(simD <= obsD ) + 1),(sum(simD >= obsD ) + 1))*2/(length(simD) + 1)= (0+1)*2/(100+1)=2/101=0.0198
Species & climate example data:
Broennimann O. , Fitzpatrick M.C. , Pearman P.B. , Petitpierre B. , Pellissier L. , Yoccoz N.G. , Thuiller W. , Fortin M.J. , Randin C.R. , Zimmermann N.E. , Graham C.H. , Guisan A. 2012. Measuring ecological niche overlap from occurrence and spatial environmental data. Global Ecology and Biogeography 21(4): 481-497. DOI
Credits : Thanks to acknowledge Andy and Stu in any related publication ! Contact weiss.andrew (a) epamail.epa.gov.
canogen.zip (4 Ko)