
BiodiversityR versions

	This ChangeLog provides information on new functions integrated in the package and some 
	required updates. Updates related to error messages for new versions of the base and 
	loaded packages are typically not included here (as these were addressed).

	BiodiversityR details on installation are available from:
	http://www.worldagroforestry.org/output/tree-diversity-analysis

	The manual accompanying the original version of BiodiversityR is available from:
	http://www.worldagroforestry.org/downloads/Publications/PDFS/B13695.pdf

	An article that documents the ensemble suitability modelling options of BiodiversityR
	is available from https://doi.org/10.1016/j.envsoft.2017.11.009



Version 2.11-3 (October 2019)

	* New function ensemble.SEDI that calculates the Symmetric Extremal Dependence Index 
	(SEDI), as formulated by Ferro et al. 2011. Wea. Forecasting 26: 699-713 and
	recommended as evaluation metric by Wunderlich et al. 2019. Nature Conservation 35: 
	97-116.

	* New function ensemble.evaluate that calculates the following evaluation statistics:
	AUC: Area Under The Curve for the testing ModelEvaluation; TSS: maximum value of the 
	True Skill Statistic over range of threshold values; SEDI: maximum value of the 
	Symmetric Extremal Dependence Index over range of threshold values; TSS.fixed: True 
	Skill Statistic at the fixed threshold value; SEDI.fixed: SEDI at the fixed threshold 
	value; FNR.fixed: False Negative Rate (= omission rate) at the fixed threshold value; 
	MCR.fixed: Missclassification Rate at the fixed threshold value; and AUCdiff: Difference
 	between AUC for calibration and the testing data 

	* Internally call ensemble.evaluate in function ensemble.calibrate.models

	* New function ensemble.VIF.dataframe that provides similar types of Variance Inflation
	Factor analysis for a data.frame as function ensemble.VIF

	* Decreased the step size for PresenceAbsence threshold calculations in function
	ensemble.threshold from 0.005 to 0.0001 (as in dismo::evaluate)

	* Corrected an error in function ensemble.mean when RASTER.stack.name=""

	* Methods and examples of generating and using spatial folds for presence and absence
	points via the blockCV package are available from the BiodiversityRblockCV package 
	(URL https://github.com/RoelandKindt/BiodiversityRblockCV) through functions 
	ensemble.spatialBlock and ensemble.envBlock (These functions are in a
	separate package as blockCV is not available from CRAN). Use the commands
	devtools::install_github("rvalavi/blockCV") and
	devtools::install_github("RoelandKindt/BiodiversityRblockCV") to install these packages.

	* example of calculating diversity profiles from importance values calculated with
	importancevalue.comp (email exchange with Uday Pimple)


Version 2.11-2 (June 2019)

	* new function ensemble.environmentalThin.clara that enables environmental thinning for
	large data sets. Prior to using function ensemble.environmentalThin internally in the 
	function, the points are first divided in clusters via the cluster.clara function. 
	Subsequently points in each cluster are environmentally thinned.
		
	* new option for ensemble.calibrate.weights to import k-fold groupings for presence and
	background points as a list with elements groupp (k-fold groupings for presence points)
	and groupa (k-fold groupings for background points). The option was inspired on using
	outputs from the blockCV package. The option is invoked by using the list as input for
	argument k of ensemble.calibrate.weights. 

	* modification in ensemble.environmentalThin to provide a final data set that matches
	the requested number of environmentally thinned points (previously the function stopped
	the second algorithm when the identified minimum distance was reached, in analogy to 
	the ensemble.spatialThin function).

	* modification in ensemble.environmentalThin to possibly retain only 1 axis if the 
	variance on 1 axis exceeds the selected threshold (the previous behaviour was to 
	select a minimum of 2 PCA axes).

	* new argument 'silent' for the ensemble.spatialThin, ensemble.environmentalThin and
	ensemble.spatialThin.quant functions, with option to have no reports on the processing
	of points.

	* new arguments 'cex.lab' and 'cex.axis' for the accumplot and accumcomp functions to 
	modify sizes of axis labels (requested by Julio Cesar Canales).

	* new options for the unconstrained and constrained ordination GUI to create 
	3-dimensional ordination graphics via the ordiplot3d, ordirgl, orglspider and 
	orglellipse functions of the vegan3d package.

	* additional options of 'ward.D', 'ward.D2' and 'mcquitty' for the cluster GUI.

	* new option 'labels (variable)' of the cluster GUI to change labels in dendrograms
	to data from the environmental data set.

	* new option in the Analysis of species abundance menu to summarize differences in 
	abundance with the Rmisc::summarySE function.

	* corrected an error in the ensemble.raster function where projection ran into problems
	with CATCH.OFF=FALSE for the GBM algorithm.

	* corrected the error of having no visible global definitions for 'data' and 
	'wrld_simpl' of the ensemble.plot function (error reported in the CRAN Package Check
	results)
	
	* corrected an error for the envfit plotting option of the ordination GUI where results
	of permutation tests were not shown

	* compatible with Rcmdr 2.5-3 (May 2019)


Version 2.11-1 (January 2019; Ty Segall & White Fence's Joy version)

	* new function ensemble.environmentalThin that provides a method similar to function
	ensemble.spatialThin, but operates in environmental instead of geographical space. The
	environmental space is represented by principal components obtained via vegan::rda.
	The user needs to define the target number of environmentally thinned points instead
	of the minimum distance.

	* new function ensemble.outlierThin that filters out point observations that could be
	outliers based on a Local Outlier Factor analysis.

	* new function ensemble.spatialThin.bins that enables spatial thinning for large data
	sets. With the function, points are first classified in different bins. In the next
	step, spatial thinning is done for each bin. Bins are defined by quantile limits of
	geographical coordinates.

	* new argument of 'MAXNET' in ensemble.calibrate.models, ensemble.calibrate.weights, 
	ensemble.raster, ensemble.batch, ensemble.drop1, evaluation.strip.data and 
	evaluation.strip.plot functions, allowing for maximum entropy species distribution 
	modeling using glmnet for model fitting as implemented in the maxnet package.

	* new argument of 'CF' in ensemble.calibrate.models, ensemble.calibrate.weights, 
	ensemble.raster, ensemble.batch, ensemble.drop1, evaluation.strip.data and 
	evaluation.strip.plot functions, allowing for  random forest and bagging ensemble 
	algorithms utilizing conditional inference trees as base learners as implemented in the 
	party package. (Note that integration of cforest required modifications of 
	raster::predict that were integrated in raster version 2.8-19.)

	* new argument of 'target.groups' in ensemble.calibrate.models, 
	ensemble.calibrate.weights, ensemble.batch and ensemble.drop1 that results in 'target
	groups' of species that were all collected or observed using the same methods or
	equipment as for the species for which species distribution models are calibrated.
	See Phillips et al. 2009 https://doi.org/10.1890/07-2153.1 for details. When selecting 
	the option, users should provide the presence locations of the other species as
	background. For model calibrations and evaluations, pseudo-absence locations will 
	correspond to centres of cells with presence locations of the other species, possibly
	excluding cells where the focal species occurs (a similar option is available from
	dismo::randomPoints). Feature requested by Tobias Fremout.

	* new argument of 'block.default' in ensemble.calibrate.weights and ensemble.batch that
	results in different options of blocking point data sets (first by latitude as only 
	option available from ENMeval::get.block [i.e. the default], or first by longitude).
	Feature suggested by Evert Thomas.

	* new argument of 'get.subblocks' in ensemble.calibrate.weights and ensemble.batch that
	results in a double implementation of ENMeval::get.block, whereby point data sets 
	assigned to one block in the first step are again assigned to four blocks ('subblocks')
	in a second step.

	* corrected error in ensemble.spatialThin to allow retaining only 1 point in case that
	the random elimination process retained two points above the minimum distance in the
	previous elimination step.

	* modified ensemble.spatialThin to round geographical distances to 2 decimals (10 m)	

	* ensured that ensemble.raster function only retained numeric variables for maxlike and
	glmnet algorithms in situations where categorical variables were used by other 
	algorithms.

	* corrected error for GBMSTEP and probit links where the gbm.x argument did not select
	the correct explanatory variables

	* compatible with Rcmdr 2.5-1 (September 2018)

	* new option in the GUI to import Excel data sets via readxl::read_excel

	* modified edit of community and environmental data sets in the GUI to be more
	similar to edit options of the R-Commander

	* new GUI for spatial and environmental thinning of point observation data


Version 2.10-1 (July 2018)

	* new function ensemble.red that calculates statistics of Area of Occupancy (AOO) and
	Extent of Occurrence (EOO) that are used as thresholds for the IUCN Red List (URL 
	http://www.iucnredlist.org/static/categories_criteria_3_1). AOO and EOO are expected
	to be calculated for 'count' suitability layers that represent different levels of 
	consensus among ensembles or algorithms. AOO and EOO are calculated via the red package.

	* new functions ensemble.chull.create and ensemble.chull.apply that restrict suitable
	habitat to polygons that are included in a convex hull around known presence locations.
	The convex hull is expanded by a user-defined buffer based on the maximum distance among
	the known presence locations.

	* new function ensemble.pairs that creates scatterplots similar to graphics::pairs

	* new function BiodiversityR.changeLog

	* corrected error in ensemble.VIF where keeping explanatory variables resulted in 
	never-ending loops if VIF of some kept explanatory variables was above VIF.max

	* compatible with Rcmdr 2.4-4 (April 2018)

	* Species accumulation GUI plots horizontal error bars (via argument ci.length for 
	plotting of specaccum objects)

	* Distance matrix calculation GUI now includes the possibily to directly calculate the
	Hellinger and Chord distances.

	* Distance matrix calculation GUI now includes the scaled Hellinder and Chord distances
	(Conde and Dominguez 2018. https://doi.org/10.1016/j.japb.2018.01.001).

	* Clark's 1952 coefficient of divergence (appropriate for the analysis of species 
	abundance data; Legendre and Legendre 2012 p. 306) was included among the options
	in distance, ordination and clustering GUIs.

	* vegan::avgdist function was included as option in the Distance matrix calculation GUI

	* vegan::chaodist function was included as option in the Distance matrix calculation GUI

	* Ensemble suitability modeling GUI now allows for the option that absence locations
	are NULL - i.e. allowing for random selection of background locations during each run.

	* Corrected error generated by constrained ordination GUI by calling vegan::goodness for
	capscale results (this option is no longer available for vegan >= 2.5-1).

	* Corrected errors generated by constrained ordination GUI by calling vegan::inertcomp
	in vegan >= 2.5-1


Version 2.9-2 (27 February 2018)

	* modified gam (version 1.13 of 2018-02-25) functions to gam::predict.Gam and 
	gam::step.Gam in ensemble.calibrate.models, ensemble.raster and evaluation.strip.data
	to safely retain BiodiversityR on CRAN (problems reported on 2018-02-26).

	* corrected error in for R-devel for rankabuncomp

	* new argument 'srt' for rankabunplot to allow rotation of species labels in rank-
	abundance graphs

	* new method 'max' for diversityresult and diversitycomp functions


Version 2.9-1 (February 2018; Ty Segall's Freedom's Goblin version)

	* new function ensemble.spatialThin that creates a spatially thinned point location
	data set where all pairwise distances are above a threshold distance. Although similar
	to functions in the spThin or red packages, the geodesic is calculated more accurately
	via the geosphere package. The function was documented separately and also was 
	integrated in the ensemble.batch function.

	* an article that documents the ensemble suitability modelling options of BiodiversityR
	has been published (Kindt R. 2018. Ensemble species distribution modelling with 
	transformed suitability values. Environmental Modelling & Software 100: 136-145. URL 
	https://doi.org/10.1016/j.envsoft.2017.11.009. References to this article has been
	included in the documentation of various functions.

	* a new argument of 'keep' in ensemble.VIF allows to always keep a subset of
	explanatory variables within the final subset of variables

	* in the output of the ensemble.mean function, niche overlap between input suitability
	layers and the mean (consensus) layer is calculated via Warren's I index that is based
	on the Hellinger distance (dismo::nicheOverlap; Warren et al. 2008. Evolution 
	62-11: 2868–2883)

	* in the ensemble.batch function, random selection of background locations (if an 
	option) is repeated in each run

	* included options in ensemble.plot to specify colours for absence and presence 
	suitabilities, including a new option only to plot areas where the species is predicted
	to be present. (Also included an example how to generate the colour scheme used in the
	http://www.worldagroforestry.org/atlas-central-america climate change atlas.)

	* It is now possible to disable calls to the tryCatch function in the ensemble 
	suitability (parameter CATCH.OFF). This option was implemented to facilitate error 
	checking (such as problems when not all packages were installed).

	* An error was encountered when attempting to plot evaluation results. This error seems
	to be caused by interpretation of the ModelEvaluation signature. The error was 
	circumvened by disabling plotting in the ensemble functions, but giving an example of
	getting plot results in the examples. Error reported by Thomas Fremout 22-JAN-2018.

	* the location of the dismo examples folder is provided explicitly in the GUI for 
	creation of raster stacks


Version 2.8-4 (September 2017)

	* compatible with Rcmdr 2.4-0 (August 2017)


Version 2.8-3 (June 2017)

	* corrected error that prevented loading of the Graphical User Interface after previous
		workspace was saved

	* corrected error in function multiconstrained

	* option added of method="dbrda" in function multiconstrained


Version 2.8-2 (May 2017)

	* full integration of the MAXLIKE algorithm in ensemble suitability modelling

	* new argument of 'get.block' in ensemble.calibrate.weights and ensemble.batch. 
		The argument splits 4-fold cross-validation presence and background point 
		location data sets along longitudinaland latidudinal lines through function 
		get.block of the ENMeval package.

	* new argument of 'mmax' in the CAPdiscrim function. This argument limits the search for
		the optimal m (number of PCoA axes) to a a maximum number of axes equal to mmax.
		The argument was introduced to deal with the lda error of a variable appearing 
		to be constant within groups. 

	* function CAPdiscrim saves correct predictions per factor level

	* function ordisymbol now allows different palettes

	* errors corrected in the 'diversity indices' menu in saving results in the 
		environmental data set

	* function evaluation.strip.data includes suitability values prior to the probit
		transformation. Errors obtained for MAHAL, MAHAL01 and DOMAIN algorithms were
		corrected for the same function.


Version 2.8-1 (January 2017, malaria recovery version)

	* compatible with Rcmdr	2.3-1 (October 2016)

	* BiodiversityRGUI function gives information on backward compatibility with prior
		versions of BiodiversityR

	* new function ensemble.calibrate.models that replaces function ensemble.test.
		The original name of ensemble.test originated from the first (2012) versions of 
		ensemble suitability modelling functions in BiodiversityR where both 
		ensemble.raster and ensemble test internally calibrated and evaluated (tested)
		models, but only ensemble.raster went ahead with creating suitability raster 
		layers. For possible backwards compatibility, assign 
		ensemble.test <- ensemble.calibrate.models

	* new function ensemble.calibrate.weights that replaces function ensemble.test.splits

	* slot ensemble.calibrate.weights$AUC.table (ensemble.calibrate.weights) replaces 
		ensemble.calibrate.weights$table

	* argument SSB.reduce (ensemble.calibrate.models, ensemble.batch) replaces argument 
		CIRCLES.at

	* ensemble suitability layers are now create in different 'ensemble' subfolders
		subfolder 'suitability' contains suitability layers for each ensemble
		subfolder 'presence' contains presence layers for each ensemble
		subfolder 'count' contains number of algorithms predicting presence
		subfolder 'consensussuitability' contains consensus suitability layers
		subfolder 'consensuspresence' contains consensus presence layers
		subfolder 'consensuscount' contains count of ensembles predicting presence
		subfolder 'consenssd' contains consensus standard deviation

	* new function ensemble.VIF that selects subsets of explanatory data layers until all
		Variance Inflation Factors are below a user-defined threshold (default: 10).
		By an iterative procedure, the data layer with largest VIF is removed in each
		step. The function is called from within the ensemble.batch function.

	* new function ensemble.bioclim that provides an algorithm that more closely represents
		the original BIOCLIM algorithm than function dismo::bioclim

	* new function ensemble.bioclim.graph that graph function makes graphs that show mean, 
		median, minimum, maximum and lower and upper limits for species or climates

	* new function stackcommunitydataset that creates a data.frame with separate columns
		for sites, species and abundance values (therefore the inverse function of
		makecommunitydataset). Function is useful to combine information from 
		different community data sets into one community data set.

	* new option for including the glmnet algorithm in ensemble suitability modelling. 
		Option available via argument of GLMNET in ensemble.calibrate.models, 
		ensemble.batch, GUI interface and other functions.

	* new option for including the maxlike algorithm (Royle et al. 2012. Methods in Ecology
		and Evolution) in ensemble suitability modelling. However, because the maxlike
		function does not accept data frames for model calibration and the predict
		function does not have a newdata argument, inclusion of the algorithm is 
		problematic and may often not be available (as in evaluation.strip.data)
		or fail (Roeland will write a new email to the authors of maxlike indicating
		the need to expand maxlike to handle data frames).

	* new option for including a modification of the dismo::mahal algorithm to ensure
		that predictions are within the 0 to 1 range similar to probabilities. Option
		available via argument of MAHAL01 and MAHAL.shape in ensemble.calibrate.models, 
		ensemble.batch, GUI interface and other functions with 

	* new output of the ensemble.batch function to report which ensemble had the best
		overall AUC. (This option can be used to plot count models

	* new options for ensemble.threshold
		threshold.method == "threshold2013.mean" provides the mean threshold of
			optimal thresholds identified by Liu et al. 2013. Journal of 
			Biogeography 40: 778-789
		threshold.method == "threshold2013.min" provides the minimum threshold of
			optimal thresholds identified by Liu et al. 2013. Journal of 
			Biogeography 40: 778-789		
		threshold.method == "threshold2005.mean" provides the mean threshold of
			optimal thresholds identified by Liu et al. 2005. Ecography 28: 
			385-393
		threshold.method == "threshold2005.min" provides the minimum threshold of
			optimal thresholds identified by Liu et al. 2005. Ecography 28: 
			385-393		

	* change of handling of data extraction from raster stacks with only 1 layer

	* internal change of raster extent no longer possible with main ensemble functions.
		Hence rasterstack objects should be modified prior to using them in
		ensemble functions.

	* change of implementation in ensemble.calibrate.models whereby dummy variables
		are no longer excluded for BIOCLIM and BIOCLIM.O algorithms

	* change of implementatin in ensemble.calibrate.models whereby only dummy variables
		with no variation are excluded for the DOMAIN algorithm

	* new option for ensemble.drop1 to also fit models with only the focal variable.
		Option available via argument of variables.alone = TRUE.

	* new option for ensemble.novel.object to exclude factor variables. The documentation
		was updated to show dealing with factor variable through dummy variables.

	* new option for ensemble.dummy.variables to create dummy variables for levels not
		observed in the input factor layer

	* increased output of ensemble.calibrate.models and ensemble.calibrate.weights to
		show how ensemble weights are determined (input weights, parameters and
		output weights)

	* warning message in ensemble GUI that title of calibration stack is expected to be
		the same as object name of the calibration stack

	* ensemble suitability calibration modelling allows to set VIF.max (maximum Variance
		Inflaction Factors of explanatory variables) and CIRCLES.d (the distance in m
		of circular neighbourhoods for testing background locations to reduce spatial
		sorting bias).

	* added example of superimposing GBIF locations in ensemble.ecocrop documentation

	* GUI option of showing calibration stack also provides names of factor variables,
		names of dummy variables and makes a plot of the calibration stack

	* Diversity indices menu now also accepts two factor variables to create a 2-way
		table with diversity statistics for each combination of factor levels

	* Added links from the GUI help to vignettes on diversity analysis in vegan and 
		ordination analysis in vegan. Also added link to the community analysis
		website of Jari Oksanen from the GUI help.


Version 2.7-2 (August 2016)

	* compatible with Rcmdr	2.3-0 (August 2016) and vegan 2.4-0 (June 2016)

	* new function ensemble.threshold to calculate threshold values to differentiate
		between absence and presence suitabilities. This function was used earlier
		only internally in the ensemble.test, ensemble.test.splits and ensemble.batch
		functions, whereas it is now available and documented as separarte function.

	* corrected error in makecommunitydataset (error reported by Pascal Hirsch)

	* Graphical User Interface (GUI) now supports following functions or options from 
	vegan:

		o dispweight function (via Transform community matrix menu)
		o fitspecaccum function (via options of "arrhenius", "gleason", "gitay", 
			"lomolino", "asymp", "gompertz", "michaelis-menten", "logis" and 
			"weibull" in Species accumulation curves menu)
		o specslope function (via options in Species accumulation curves menu)
		o rareslope function (via options in Species accumulation curves menu)
		o rarefy function  (via options in Species accumulation curves menu)
		o tsallis function (via options in Renyi profile menu)
		o tsallisaccum function (via options in Renyi profile menu)	
		o dbrda function (via Constrained ordination menu)
		o monoMDS function (via Unconstrained ordination menu)
		o stressplot function (via unconstrained and constrained ordination menus)
		o betadisper function (via Compare distance matrices menu)
		o designdist function (in Distance matrix calculation menu)
		o Lingoes and Cailliez adjustments for wcmdscale, capscale, dbrda and 
			betadisper
		o sqrt.dist argument for wcmdscale, capscale, dbrda and betadisper
		o descriptive string of "species" in scaling of ordination axes (via
			unconstrained and constrained ordination menus)
		o RsquareAdj function for cca, dbrda and capscale (in summaries of constrained 
			ordination)
		o ordibar function (via plotting functions for unconstrained and constrained
			ordination)
		o plotting factor levels in different colours with ordihull, ordiarrows, 
			ordisegments, ordispider, ordibar and ordiellipse (via plotting 
			functions for unconstrained and contrained ordination)
		o summary and ordiareatest for ordihull and ordiellipse (via plotting 
			functions for unconstrained and contrained ordination)
		o ehull option of ordiellipse ((via plotting functions for unconstrained 
			and contrained ordination))

	* change in calculation for ensemble.threshold function when using thresholds from the
		PresenceAbsence package with ensemble.threshold options of "threshold.mean"
		and "threshold.min": five thresholds from the PresenceAbsence package will
		be used (see Details)

	* new parameter ENSEMBLE.weight.min to set minimum output weight for ensemble.test,
		ensemble.test.splits and ensemble.batch. Note that parameter ENSEMBLE.min
		refers to the minimum input weight (and typically used to exclude algorithms
		with low AUC values).

	* ensemble.plot allows to add country boundaries (via maptools package)

	* ensemble.plot exports breaks and colours if only one suitability map is plotted

	* breaks are forced to be unique in ensemble.plot

	* ensemble.analogue gives warning is variables are very strongly correlated with 
	method 'mahal' (as algorithm my fail)

	* corrected problem in ensemble.novel function when x only has one layer

	* avoid error when launching the GUI when dismo package was not installed

	* corrected error in labeling the y-axis in reyniplot function (error reported by
	Mauricio Carrasquilla)


Version 2.7-1 (April 2016)

	* ensemble.batch: procedure stops when no algorithms retained in the k-fold
	cross-validation procedure

	* new Graphical User Interface (GUI) for renaming layer names of calibration
	and prediction stacks

	* included link to Hijmans RJ and Elith J. 2016. Species distribution modelling with R.	

	* options to set width and height of new graphical device for ensemble.plot,
	evaluation.strip.plot and ensemble.centroids functions. Setting any of these parameters
	to a value < 0 results in no opening of a new device .


Version 2.7-0 (March 2016)

	* new Graphical User Interface (GUI) for ensemble suitability modelling.
	Guidelines for getting started are available from the GUI and in the 'doc'
	folder of BiodiversityR

	* included the ensemble.mean function within ensemble.batch, so that
	ensemble.batch also produces the mean ('_MEAN_') ensemble files when several
	ensembles are calibrated via ensemble.batch

	* new function ensemble.plot, especially to apply a colourscheme that
	differentiates between suitabilities below and above a threshold that
	discriminates between predicted absence-presence of the organism

	* new feature in the evaluation.strip.plot to include a boxplot for the 
	presence locations of a data set used for model calibrations

	* included help buttons in various GUI windows


Version 2.6-1 (January 2016)

	* ensemble.centroid and ensemble.zones: New functions to determine centroid 
	locations in principal components space of presence locations of an organism. 
	Mahalanobis distance from centroid locations to map zones based on the
	minimum distance from centroid locations.

	* report information on spatial sorting bias in ensemble.test.

	* CIRLES.at and CIRCLES.d options in ensemble.test function to reduce spatial 
	sorting bias between evaluation presence and absence locations

	* threshold.PresenceAbsence option in ensemble.test to use the PresenceAbsence
	package to calculate absence-presence thresholds.
	
	* ensemble.novel: New function to map novel environmental conditions.
	
	* ensemble.area: New function to calculate areas of suitability raster maps.

	* ensemble.analogue: New function to map environmental (climate) analogues.
	
	* ensemble.ecocrop: New function to map suitability based on temperature 
	and rainfall optimal and absolute ranges.

	* corrected problem in handling probit-transformations in ensemble.raster function

	* started ChangeLog


Version 2.5-4 (September 2015)

	* compatibility with Rcmdr restored (eg qqPlot)

	* menu interface scripts updated	

	* new menu option of Analysis of diversity > Add diversity variables to data set

	* new menu option of silhouette in the Cluster analysis plot options


Version 2.5-3 (July 2015)

	* changes in the CAPdiscrim function to result in same results as PRIMER (problem
	handled by including as.dist() function prior to cmdscale() function).

	* new function importancevalue to calculate Importance Value Index, and new
	ifri data set (collaboration with the International Forestry Resources and Institutions 
	[IFRI] research network; http://www.ifriresearch.net)  

	* new menu option of replacing NA with 0 in the community data set

	* corrected problem in ensemble.test.splits function in obtain AUC-derived
	weights for submodels when weights are not tuned

	* ensured that subfolder to save models is created (ensemble.test function)
	
	* included package information for function visibility


Version 2-5.2 (April 2015)

	* included droplevels() function in function ensemble.test

	* avoiding loading of libraries in ensemble functions (including gam::s()
	for gam formula)

	* included topography-derived variables in BCI.env data (provided by P. Legendre)


Version 2-5.1 (November 2014)

	* menu option to remove species with zero total abundance

	* handle new 8-character species codes in vegan in examples

	* include options to plot as.phylo() cluster dendrograms

	* option to reorder cluster dendrograms

	* option to plot symbols in cluster diagrams

	* BiodiversityR start up message

	* expand vegan functions from menu interface (vegemite, tabasco, coverscale,
	screeplot, bioenv, betadisper, contribdiv, beals, betadiverr, wcmscale, pcnm,
	polaccum, estaccumR, eventstar, indpower, isomap, meandist, nestedchecker,
	nestedtemp, nestednodf, nestedbetasor, nestedbetajac, RsquareAdj, drarefy,
	simper, treeheight)

	* corrected problems with jackknife of diversity analysis (diversityresult
	function with method='jackknife')


Version 2-4.4 (May 2014)

	* new PROBIT option in ensemble.test function to transform outputs of 
	ensemble submodels with probit transformation (also supported in 
	ensemble.raster function)	

	* new ENSEMBLE.exponent option to modify weights of ensemble submodels
	in ensemble model by using exponent

	* corrected use of persp() for accumulated renyi profiles in menu interface


Version 2-4.1 (January 2014)

	* new functions of ensemble.simplified.categories and ensemble.dummy.variables

	* new function of ensemble.evaluation.strip

	* only allow ensemble calibration in ensemble.test and ensemble.test.splits
	functions

	* include legends in menu-interface generated plots no longer via locator()

Older versions

	* mainly changes related to newer version of R base and loaded packages,
	including changes required to maintain compatility with R-commander


