Virtual Reality of the Niche Theory

Version 1.02

BIODIVERSITY INFORMATIC APPLICATION Virtual Reality of the Niche Theory

Niche Analyst User Guide

1 BIODIVERSITY INFORMATIC APPLICATION Niche Analyst

Huijie Qiao, Jorge Soberón, Lindsay Campbell & A. Townsend Peterson mailto:[email protected]

 Biodiversity Institute, University of Kansas 1345 Jayhawk Blvd. Lawrence, KS, 66045-7593 USA  Key Laboratory of Animal Ecology and Conservation Biology, Chinese Academy of Sciences 1 Beichen West Road, Chaoyang District, Beijing 100101, P.R.China

October 3, 2012

------FOREWORD ------The Niche Analyst (NicheA) User Guide provides a detailed overview of NicheA, the application in ecological niche analysis. It was thought as a comprehensive, fully-searchable, self-contained, annotatable manual. Its latest version can always be obtained from a website (a website). The source files are available through a subversion version control repository at svn://mmweb.animal.net.cn/nichea/trunk. Given NicheA’s heavy development this guide will always remain incomplete. All NicheA users and developers are encouraged to contribute to the NicheA documentation resources.

Table of Contents

1. INTRODUCTION TO NICHEA ...... 1

1.1 WHAT’S NICHEA ...... 1 1.2 SUPPORTED PLATFORMS ...... 5 1.3 REQUIREMENTS ...... 7 2. INSTALLATION ...... 7

2.1 INSTALLING ON WINDOWS ...... 8 2.2 INSTALLING ON MAC OS X ...... 8 2.3 INSTALLING ON LINUX ...... 9 3. RUNNING NICHEA ...... 10

3.1 LAUNCH NICHEA FOR THE FIRST TIME ...... 10 3.2 THE GRAPHICAL USER INTERFACE ...... 11 Main Menu: ...... 11 Widget: ...... 11 3.3 CREATING YOUR FIRST BACKGROUND CLOUD ...... 12 Definition ...... 12 Creating a BC ...... 12 3.4 PLAYING WITH SDS ...... 16 Definition ...... 16 Creating a SDS ...... 17 Displaying a SDS ...... 18 Designing barrier ...... 21 3.5 INTERACTING WITH OTHER ENMS ...... 23 4. FUNCTION LIST ...... 24 1. Generating principal components ...... 24 2. Quantifying niche similarity ...... 24 3. ES viewer and widgets ...... 24 4. Generating a SDS ...... 25 5. GS viewer ...... 25 6. Conversion tool ...... 25 7. Interacting with other ENMs ...... 25 5. FAQ ...... 25 6. CITING NICHEA ...... 25 7. REFERENCES ...... 25 8. SUPPORTED FORMATS IN NICHEA ...... 27 9. ACKNOWLEDGEMENTS ...... 28

hanks for using NicheA! At present, this software should be considered an alpha release – some bits aren’t meant to be used yet, and it hasn’t been extensively user-proofed yet. It’s still entirely possible to tell the software to do things that it shouldn’t do, which will produce nonsense results (Robbed from ENMTools. *_^).

1. Introduction to NicheA

1.1 What’s NicheA

Niche Analyst (NicheA; https://sourceforge.net/p/nichea/) is an open-source, cross-platform application released under a GNU Public License (GPL). NicheA is written in Java, combining several toolkits, such as R (R Development Core Team 2011), Weka (Hall 2009), JAMA (Hicklin et al. 2012), GDAL (GDAL Development Team 2011) and QuickHull3D (Lloyd 2012; Fig. 1). The platform is a window-based, user-friendly application that executes on most common operating systems, including Microsoft Windows, Mac OS X, and some Linux releases, such as Ubuntu.

Users can use NicheA (1) to re-orient and re-cast environmental variables through principal component analysis (PCA), (2) visualize species’ distributions in linked E and G spaces, (3) design barriers to dispersal in G, (4) estimate and display Grinnellian niches in E, and (5) map objects between G and E. Fig. 2 shows functions and feasible action flows in NicheA. NicheA can also import and display results of widely-used ENMs, and export SDSs in formats compatible with various ENM platforms.

The unique functionality in NicheA, not available in other software programs, is that of estimating Grinnellian niches of species based on environmental variables and occurrence records, but with a clear focus on fundamental ecological niches. We have implemented two algorithms, a minimum volume ellipsoid (MVE; Van Aelst & Rousseeuw 2009) and a convex hull (Lloyd 2012), both designed to approximate the full dimensions of fundamental niches via approximation of convex shapes in multivariate environmental spaces. NicheA can display ecological niches; calculate their shape, density, location, and other attributes; and quantify similarity among multiple niches based on MVE overlap. A few studies have used convex hulls to

estimate niches (Rissler & Apodaca 2007; Monahan & Tingley 2012), but this approach has not been implemented easily owing to the complexity of its formulas.

Fig. 1. The software architecture of NicheA. NicheA is a multi-language, GUI-based application that invokes four graphics libraries to implement user interactions. Function modules handle messages sent from the GUI, invoke libraries to complete calculations, and return results to the

GUI.

Fig. 2. Feasible action flows in NicheA. Four function modules in NicheA: (1) The left block is the workflow for creating and displaying background cloud with environmental layers supplied by the user. (2) The second block shows generation of SDSs, displaying them in E, and computing their attributions. (3) The third block shows a simple function used to design barriers for SDSs in G. (4) The final block contains processes for interacting with other ENM algorithms.

Table 1: The functions in NicheA Group Name Description E Viewer NicheA can display MVEs, convex hulls, occurrence points and background cloud (BC) in this 3D space. The user can change the perspective by dragging the scenario with the mouse, zoom in/out by dragging the scenario with alt + mouse, and move the scenario with Win (Command) + mouse. Widgets Use to create an ellipsoid with the specified center, semi-axis, and rotations.

G Viewer and tools Display a geography map of an SDS. The barrier designer can be used to create a barrier in G, split the SDS into two subsets (in/out), and to create a new SDS. File Control Open an SDS (1) “SDS Folder”: Select a folder as an SDS, calculate MVE and convex hull, and display them in the E. (2) “GeoTIFF File”: Use a raster file as an SDS, and execute the same steps with “SDS Folder”. This function can be used to display and analyze ENM results. Close SDS(s) Close the opened SDS(s) Clear scenario Close all the opened SDS and clear BC. Save the current Save the current selector to a file with the extension ‘elp’. selector Open a selector Open a saved selector configuration file. Open multiple Open multiple selector configuration files at the same selectors time. Draw BC Load data in a fixed-structured folder and draw the BC in E. The function “Generate principal components” can create BC configuration folder. Draw BC from three Select three variables and draw them in E as a BC environmental layers directly. Close Exit the application. Tools Create a virtual SDS Create a virtual SDS based on the BC and the ellipsoid. The points inside the ellipsoid are regarded as the occurrences of the virtual species. The virtual SDS will be saved in the selected folder with the fixed format. Generate an SDS Generate an SDS via the occurrences in a BC. Quantify niche Quantify niche similarity of two species or two niche similarity types by calculating the overlap of two MVEs. Draw an overlap Invoke the function “Quantify niche similarity” to calculate the related information and draw the results in E. Design barriers Map the select SDS to G, and create a barrier with a polygon in G. Generate principal Calculate and create principal components for a selection

components of environmental variables. Conversion tool for Convert the format of a raster file to GeoTIFF or ASCII raster file raster grid from other supported formats. All the supported format are listed at http://www.gdal.org/formats_list.html Control Show/hide point Show or hide the points of all the SDSs in E. Show/hide MVE Show or hide the MVE of all the SDSs in E. Show/hide grid Show or hide a grid in E. Show/hide BC Show or hide the BC in E. Show/hide convex hull Show or hide the convex hull of all the SDSs in E. Show/hide selector Show or hide the selector in E. Reset Return to default settings. SDS(s) A list of all the opened SDS. About About Some information about this software.

1.2 Supported Platforms

NicheA provides support for most of the popular operating systems. If you want to know if NicheA supports a particular platform, please contact us. NicheA will run on: • Windows XP, Vista, Windows 7 (Fig. 3) • Mac OS X (Intel) 10.6 and later (Fig. 4) • Linux (Intel x86/x64) Some distributions and version such as Ubuntu 12 (Fig. 5)

Fig. 3 NicheA on Windows xp

Fig. 4 NicheA on Mac OS X Lion

Fig. 5 NicheA on Ubuntu 12

1.3 Requirements

NicheA requires some extend tools to handle the raster file or some other functions. Before running NicheA, you need to install the following software ahead. • JRE 1.6+: http://www.oracle.com/technetwork/java/javase/downloads/index.html • Java 3D: http://www.oracle.com/technetwork/java/javase/tech/index-jsp-138252.html • GDAL: http://www.gdal.org/ • R: http://www.r-project.org/ • ImageMagick: http://www.imagemagick.org/script/index.php

2. Installation NicheA is a cross-platform tool under the Java Virtual Machine environment. Before running NicheA, you need to install the software in “Requirements” sections, and make sure they can work well.

This section describes how to get up and run with NicheA on a variety of platforms. Each required software has its user manual. User can follow it to install them to the different platform. In this document, we pointed out the matters for attention of each platform only.

2.1 Installing on Windows

• GDAL GDAL development team provides full-functions executable package for Windows. With this package, user can run NicheA in an SDK shell of NicheA directly. This package can be downloaded via http://www.gisinternals.com/sdk/. • Java 3D This release of Java 3D runs on JDK version 1.5.0 and higher. To install this build, execute the binary installer that you downloaded, by double-clicking on the java3d-1_5_1-windows-i586.exe (or java3d-1_5_1-windows-amd64.exe) icon and following the steps. • ImageMagick You can download and install the static installation version via http://www.imagemagick.org/script/binary-releases.php#windows to your computer. Notic: DON’T install ImageMagick to the default location, suck as “C:\Program Files\ImageMagick”. Install ImageMagick to a location without any WHITE SPACE in its path, or it will bring some unknown errors to NicheA. • R Download and install R via http://www.r-project.org/. The installation path must NOT contain a WHITE SPACE, either.

2.2 Installing on Mac OS X

All the tools above have the Mac version. Download and install them one by one except GDAL. Or you can install the software with MacPorts (http://www.macports.org/). • GDAL

Because NicheA invokes the GDAL XCode Dynamic Library file (“*.dylib”) to handle the raster files, it is necessary to compile and install GDAL from source code. The source code of GDAL can be found at http://trac.osgeo.org/gdal/wiki/DownloadSource. And there is an installation guideline at http://trac.osgeo.org/gdal/wiki/BuildHints. Because there has been a compiled Dynamic-link library (“.dll”) in GDAL’s Windows installation package, you needn’t install GDAL from source code in Windows.

2.3 Installing on Linux

All the tools above have the Linux version. Download and install them one by one except GDAL. Or you can install the software with some package management tools based on your OS, such as “yum” in CentOS or “apt-get” in Ubuntu. • GDAL Because NicheA invokes the GDAL Unix Shared Library (“*.so”) to handle the raster files, it is necessary to compile and install GDAL from source code. The source code of GDAL can be found at http://trac.osgeo.org/gdal/wiki/DownloadSource. And there is an installation guideline at http://trac.osgeo.org/gdal/wiki/BuildHints.

Tips:

• If you get an exception caused by “java.lang.NoClassDefFoundError: javax/media/j3d/Node” when you launch NicheA, you should copy some JAR (Java Archive, *.jar) files to your Java library manually.

♦ Windows: Copy all the files in “C:\Program Files\Java\Java3D\1.5.2” to “C:\Program Files\Java\jre6 (or 7)”

♦ Mac OS X: Copy the JAR file in the downloaded zip file to “/System/Library/Java/Extensions”

♦ Linux: The paths are different with the release versions and the Java’s version. For example, the path of Ubuntu with Oracle Java 7 is “/usr/lib/jvm/java-7-oracle/jre/lib/ext”

3. Running NicheA

3.1 Launch NicheA for the first time

It’s suggested to execute the NicheA from a terminal with the following steps: 1. Open a terminal • Windows: Start -> Run -> input “cmd” and press “Enter” • Max OS X: Finder -> Applications -> Utilities -> Terminal.app 2. Run NicheA with this command: java -jar -Djava.library.path=[Path to gdal java library] nichea.jar When you run NicheA for the first time, NicheA will popup a configuration form to set the parameters (Fig. 6). In this form, you can set the number of points for BC and SDS in ES, set the paths to the outside tools. If NicheA cannot find the tool in the specified path, the color of text field is red. You can change the parameters’ value via the “Preserences…” menu at any time.

Fig.6. The configuration form.

Tip:

• The tool’s path cannot contain any white space to avoid some unknown errors among the different operating systems.

• In Mac OS X and Linux, you can only use “/” in the path. In Windows, you can use both “/” and “\”.

• If you don’t how to set the “environmental variables” in Windows, it’s easy to get the runtime environment via double-clicking “SDKShell.bat” file in “GDAL” folder.

3.2 The Graphical User Interface

There are three parts, the main menu, a group of widgets, and the 3D space (ES) (Fig x).

Main Menu: You can find and invoke all the functions in NicheA in the main menu.

Widget: The group of widgets is used to create a selector (a white ellipsoid with four red points and a greed point) in ES. The “Offset” sliders can control the centre of the ellipsoid in three directions (X, Y, and Z). The “Zoom” sliders can set the length of the semi-axes of the ellipsoid. And the “Rotate” sliders can make the ellipsoid rotating along with the specified axis. The “Lock” checkboxes are used to avoid the misoperations by locking some of the sliders.

Figure x. The main frame.

3.3 Creating your first background cloud

Definition The background cloud (BC) is made up by a group of points in a 3D environmental space (ES). Each point has three values (x, y, z) in ES and a geographic coordinate (longitude and latitude). In other words, BS is a map of three geographic environmental variables in ES.

Creating a BC You can use an existing BC configuration to create a BC, or draw a BC with three environmental variables directly. NicheA provides the function to create a BC configuration via the “Generate principal components” function. After clicking the “Generate principal components” menu item from the main menu, NicheA will open a dialog which is used to select multiply GeoTIFF files to generate the principal components with them (Fig. x). The generated principal components (a series of GeoTIFF files) will be stored in the specified folder. The loading of each principal component is

saved in a text file (“loading.txt”), and a BC configuration is saved in the “background” folder which contains the information of the first three principal components and can be used to draw the BC directly (Fig. x).

Fig. x The configuration form for “Generate principal components” function

Fig. X The result of “Generate principal components” function After generating the principal components, you can draw BC with the BC configuration in the “background” folder (Fig. x) or any three principal components (Fig. x).

Fig. x Draw BC with a configuration “folder”

Fig. x Draw BC with three variables

Fig. x a sample BC in ES

Tips:

• The environmental layers used to calculate the principal components or draw the background cloud must have the same geographical attributions (the projection method, the size, and so on). Or it will lead some unknown errors and strange results.

• There is only one BC for a scenario. If you want to change another BC, you can only close and reopen NicheA.

3.4 Playing with SDS

Definition A species data set (SDS) can be either a special folder with four files (Table. X) or a raster file with a threshold. NicheA can display both of them in ES, calculate its MVE and convex hull, and estimate the overlap of two SDSs’ MVEs or convex hulls.

File name Description Optional A text file contains the geographic coordinates of a species. ll.txt Yes (longitude, latitude) xy.txt A text file contains the plane coordinates of a species. (x, y) Yes value.txt A text file contains values of three dimensions. Yes A GeoTIFF file represents the species’ distribution in geographical present.tiff No space. An image represents the species’ distribution in geographical present.png No space. A scaled image represents the species’ distribution in present_1000.png No geographical space. An configuration file contains the information about a selector selector.elp No which can be used to draw an ellipsoid in ES.

Creating a SDS NicheA supplies three methods to create a SDS. [Method 1:] You can draw an ellipsoid (a white ellipsoid with six red vertexes and a greed centre) in ES using the widgets on the left side of GUI (Fig. x), and invoke the “Create a virtual SDS” function in the main menu. NicheA will iterate all the points in BC and create a virtual SDS with the points inside of the ellipsoid automatically. [Method 2:] If the use has a text file which contains the longitude and latitude of a species, NicheA can map the occurrences to the ES and create a SDS. [Method 3:] The raster file can also be regarded as a SDS. This raster file can be a species’ distribution or an ENM’s result. For each raster file, you must set a threshold which is used to split the raster into presence/absence groups. NicheA will seek all the points in the raster file whose value higher than the threshold, and create a SDS.

Fig. x a selector in ES (a white ellipsoid with six red vertexes and a greed centre)

Tip:

• Whenever you want, you can save the configuration of an ellipsoid (in NicheA, we call it “selector”).

• A virtual SDS contains a “selector” configuration file in its folder.

• You can open a “selector” file in ES.

Displaying a SDS After creating a SDS, you can open and draw it in ES (Fig. x). You can control the colors of MVE, convex hull and the occurrence points of the SDS. If there are more than two SDS in ES, you can calculate MVE’s overlap of any two SDS (Fig.x).

Fig.X Open a SDS

Fig. x Three opened SDSs in ES

Fig.x Calculate the overlap of two SDSs’ MVEs

Fig. x the result of the overlap of two SDSs’ MVEs

Designing barrier “Designing barrier” is one and the only function in GS. After you invoke the “Design barrier” function from the main menu, and select a SDS (Fig.x), NicheA will map the data of the selected SDS from ES to GS, and create its distribution map. In GS, you can click and drop your mouse to create a green polygon (Fig.x). After clicking the “Generate” button and input the name of the barrier, NicheA will split the SDS into two subsets (inside/outside of the polygon), create two new SDSs, and store them in a subfolder of SDS. Then you can execute all the functions in NicheA for the new data sets, such as draw MVE, calculate the overlap, and so on.

Fig.x Select a SDS to design barrier.

Fig.x a barrier of SDS in GS.

3.5 Interacting with other ENMs

NicheA can generate the necessary files and export a SDS to Maxent or openModeller (Fig.x ). And the ENMs results can be opened in NicheA as a special SDS (Fig. x). Besides the “design barrier” function, the special SDS can employ all the functions in NicheA.

Fig. X export SDS to openModeller

Fig. X open an openModeller’s result in NicheA

4. Function list 1. Generating principal components “Generating principal components” is an independent application used to calculate the principal components of multiple environmental layers with the same geographical reference systems and resolution. The principal components are stored in standard GeoTIFF and Arc/Info ASCII Grid formats that can be used in other ENMs, such as Maxent and openModeller directly. A text file with the name “proportion.txt” stores the loading value of each individual principal component. And the folder “background” can be opened as a background cloud in the ES viewer.

2. Quantifying niche similarity Differing with ENMTools, NicheA can quantify niche similarity in ES rather than GS. The niche similarity in NicheA does not come from ‘total variation distance’ (ENMTools) but from the overlap of two ellipsoids directly, which can be regarded as another measurement of niche similarity.

3. ES viewer and widgets The ES viewer is the main frame of NicheA. Users can display environmental variables, observe the location of a species in ES, and analyze relationships among environmental variables and different niche scenarios intuitively.

The gray scatter plot, referred to as the background cloud, represents the distribution of 3 environmental variables in a 3D space. Each axis corresponds to one variable. Additionally, users can assign a group of specific, true environmental variables, although we suggest using the “Generating principal components” function to avoid potential correlation between environmental variables that could bias model results and to standardize variable units for analyses.

Widgets located to the left of the ES viewer can be used to create an ellipsoid in ES, which is regarded as a formalization of the fundamental niche of a virtual species (Soberón and Nakamura 2009). With this ellipsoid, the user can create a comprehensive, theoretically based virtual species. Furthermore, the user can export the virtual species into ENMs directly. Additionally, NicheA can open a SDS prepared with the same format as exported virtual species via a specific tool, and display it in the ES viewer. For each opened SDS, NicheA can calculate and display its MVE and convex hull in ES automatically.

In the ES viewer, the user can display multiple species at the same time. Additionally, the user can calculate and display the niche overlap of any two species via the “Quantifying niche similarity” function.

4. Generating a SDS This utility is used to generate a SDS based on an occurrence record file and three environmental variable files supplied by the user. This SDS can be opened and displayed in the ES viewer in NicheA.

5. GS viewer The GS viewer is complementary to the ES viewer. The user can switch the view between GS and ES for each species. The most important function in GS is the capability to design an M scenario, conceptualized in the BAM framework. The user can draw a polygon in GS to divide a study area into two subsets.

6. Conversion tool The “Conversion tool” utility is an additional application that can be used to convert raster environmental variables to different formats, including GeoTIFF, Arc/Info ASCII Grid and ESRI Labeled EHdr.

7. Interacting with other ENMs For user convenience, the SDS can export to two formats compatible with Maxent and openModeller. Additionally, NicheA can open results from these two ENMs in ES. This function can help the user to analyze the relationship between the occurrences used for modeling and the results based on the occurrences.

5. FAQ

6. Citing NicheA

7. References Abrams, P. (1980) Some comments on measuring niche overlap. Ecology, 61, 44-49. Araújo, M.B. & Guisan, A. (2006) Five (or so) challenges for species distribution modelling. Journal of Biogeography, 33, 1677-1688. Austin, M. (2007) Species distribution models and ecological theory: a critical assessment and some possible new approaches. Ecological Modelling, 200, 1-19. Barbet-Massin, M., Jiguet, F., Albert, C.H. & Thuiller, W. (2012) Selecting pseudo-absences for species distribution models: how, where and how many? Methods in Ecology and Evolution, 3, 327-338.

Barve, N., Barve, V., Jiménez-Valverde, A., Lira-Noriega, A., Maher, S.P., Peterson, A.T., Soberón, J. & Villalobos, F. (2011) The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecological Modelling, 222, 1810-1819. Bentlage, B. & Shcheglovitova, M. (2012) NichePy: modular tools for estimating the similarity of ecological niche and species distribution models. Methods in Ecology and Evolution, 3, 484-489. Colwell, R.K. & Futuyma, D.J. (1971) On the measurement of niche breadth and overlap. Ecology, 52, 567-576. Colwell, R.K. & Rangel, T.F. (2009) Hutchinson's duality: the once and future niche. Proceedings of the National Academy of Sciences USA, 106, 19651-19658. GDAL Development Team (2011) GDAL - Geospatial Data Abstraction Library, Version 1.7.0. URL http://www.gdal.org/ [accessed 10 September, 2012] Guisan, A. & Thuiller, W. (2005) Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8, 993-1009. Hicklin, J., Moler, C., Webb, P., Boisvert, R.F., Miller, B., Pozo, R. & Remington, K. (2012) JAMA : A Java Matrix Package. National Institute of Standards and Technology, Gaithersburg. URL http://www.gdal.org/ [accessed 10 September, 2012] Hirzel, A.H. & Arlettaz, R. (2003) modeling habitat suitability for complex species distributions by environmental-distance geometric mean. Environmental Management, 32, 614-623. Hirzel, A.H., Helfer, V. & Metral, F. (2001) Assessing habitat-suitability models with a virtual species. Ecological Modelling, 145, 111-121. Holt, R.D. (2009) Bringing the Hutchinsonian niche into the 21st century: Ecological and evolutionary perspectives. Proceedings of the National Academy of Sciences USA, 106, 19659-19665. Hutchinson, G.E. (1957) Concluding Remarks. Cold Spring Harbor Symposia on Quantitative Biology, 22, 415-427. Hutchinson, G.E. (1978) An Introduction to Population Ecology. Yale University Press, New Haven. Jiménez-Valverde, A., Lobo, J.M. & Hortal, J. (2008) Not as good as they seem: the importance of concepts in species distribution modelling. Diversity and Distributions, 14, 885-890. Leibold, M.A. (1995) The niche concept revisited: mechanistic models and community context. Ecology, 76, 1371-1382. Lloyd, J. (2012) QuickHull3D: A Robust 3D Convex Hull Algorithm in Java. University of British Columbia, Vancouver. URL http://www.cs.ubc.ca/~lloyd/java/quickhull3d.html [accessed 10 September, 2012] Mark Hall, E.F., Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten (2009) The WEKA data mining software: an update. SIGKDD Explorations, 11, 10-18. Monahan, W.B. & Tingley, M.W. (2012) Niche tracking and rapid establishment of distributional equilibrium in the House Sparrow show potential responsiveness of species to climate change. PLoS ONE, 7, e42097. Muñoz, M.E.S., Giovanni, R., Siqueira, M.F., Sutton, T., Brewer, P., Pereira, R.S., Canhos, D.A.L. & Canhos, V.P. (2011) openModeller: a generic approach to species' potential distribution modelling. GeoInformatica, 15, 111-135. Pearson, R.G. (2007) Species' Distribution Modeling for Conservation Educators and Practitioners: Synthesis. American Museum of Natural History. New York.

Pearson, R.G., Raxworthy, C.J., Nakamura, M. & Peterson, A.T. (2007) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. Journal of Biogeography, 34, 102-117. Peterson, A.T. (2006a) Ecological niche modeling and spatial patterns of disease transmission. Emerging Infectious Diseases, 12, 1822-1826. Peterson, A.T. (2006b) Uses and requirements of ecological niche models and related distributional models. Biodiversity Informatics, 3, 59-72. Peterson, A.T. (2011) Ecological niche conservatism: a time-structured review of evidence. Journal of Biogeography, 38, 817-827. Phillips, S.J. & Dudík, M. (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography, 31, 161-175. Pulliam, H.R. (2000) On the relationship between niche and distribution. Ecology Letters, 3, 349-361. Rödder, D. & Engler, J.O. (2011) Quantitative metrics of overlaps in Grinnellian niches: advances and possible drawbacks. Global Ecology and Biogeography, 20, 915-927. R Development Core Team (2011) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. URL http://www.R-project.org [accessed 10 September, 2012] Rissler, L.J. & Apodaca, J.J. (2007) Adding more ecology into species delimitation: ecological niche models and phylogeography help define cryptic species in the Black Salamander (Aneides flavipunctatus). Systematic Biology, 56, 924-942. Saupe, E., Barve, V., Myers, C., Soberón, J., Barve, N., Hensz, C., Peterson, A., Owens, H. & Lira-Noriega, A. (2012) Variation in niche and distribution model performance: the need for a priori assessment of key causal factors. Ecological Modelling, 237, 11-22. Soberón, J. (2007) Grinnellian and Eltonian niches and geographic distributions of species. Ecology Letters, 10, 1115-1123. Soberón, J. & Nakamura, M. (2009) Niches and distributional areas: concepts, methods, and assumptions. Proceedings of the National Academy of Sciences USA, 106, 19644-19650. Soberón, J. & Peterson, A.T. (2005) Interpretation of models of fundamental ecological niches and species' distributional areas. Biodiversity Informatics, 1-10. Thuiller, W., Lafourcade, B., Engler, R. & Araújo, M.B. (2009) BIOMOD – a platform for ensemble forecasting of species distributions. Ecography, 32, 369-373. Van Aelst, S. & Rousseeuw, P. (2009) Minimum volume ellipsoid. Wiley Interdisciplinary Reviews: Computational Statistics, 1, 71-82. Warren, D.L., Glor, R.E. & Turelli, M. (2008) Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution, 62, 2868-2883. Warren, D.L., Glor, R.E. & Turelli, M. (2010) ENMTools: a toolbox for comparative studies of environmental niche models. Ecography, 33, 607-611.

8. Supported formats in NicheA

9. Acknowledgements