1st jaguar simulation model

With my case study involving complicated landscape structures and real-world scenarios, I needed to first get to grips with getting an agent-based model of jaguar movements up and running in a simplified landscape that would enable some interpretation of population dynamics without the need for an in-depth and overly detailed landscape.
After discussing several options, a very abstract and basic landscape structure was decided on to try to answer some fundamental questions important to my on-going research:

1) Can we get a model of jaguar movements working, with plausible daily movements and territory sizes close to those found in real world populations?

2) Does landscape structure seem to influence the way jaguars move around the landscape and does it affect the fitness of individuals and the population as a whole?

3) Can habitat corridors help to increase the connectivity of the landscape and facilitate movement of individuals between habitat patches?

9 landscape structures were defined to help explore these questions, including 3 control landscapes (top row), 3 connected corridors (middle row) and three non-connected corridors (bottom row) :

'Good' habitat here is forest (in green). This is where jaguars will prefer to be. Intermediate habitat is marked in blue, and represented edge habitat; the edge of the forest that meets the non-forest habitat. This is deemed to be less desirable than the forest itself but more desirable than the non-forest habitat. Non-forest (matrix) is coloured beige, and represents any habitat where the jaguar do not want to be; urban areas, agricultural land, roads etc etc.

Landscapes were designed to cover a range of potential options. All designs (bar the first two; the all forest and the 2 distinct habitat patches) have exactly the same amount of forest and matrix habitat. Edge habitat changes depending on the design of the landscape.

The model is designed as a grid, with individual jaguars occupying any one grid cell at a time. Least-cost methodologies are employed so that each habitat has a cost; forest of 1, edge of 5 and non-forest (or matrix) as 25. This represents the strength of the preference of jaguars to any habitat (lower cost equals a much stronger preference).


Next post - more information about jaguar movements and getting territories to develop.

Jaguars as a case study

Ok,

So now I have all things technical working and sorted I can continue discussing my actual work :)

I've mentioned that my work has its roots in ongoing fieldwork in Belize. My target species is the Jaguar: an apex predator, the third largest feline in the world (behind the lion and the tiger) and a probable keystone species: the jaguar plays an important role in stabilising and controlling the ecosystems in which they are found.

Jaguars were historically found from the southern United States to northern Argentina, although this range has been reduced but up to 40-50%, with much of the existing area more highly fragmented and vulnerable to disturbance.

Territories of typical individuals range from approximately 10-40km2 for females to 30-80 km2 for males. Density varies a lot, with maybe 0.2 per 100km2 in some areas of Brazil to 8-10 per 100km2 in the Cockscomb Basin Wildlife Sanctuary in Belize.

The main reasons for this flexibility and variability in density and territory size is thought to centre around prey density and availability and amount/quality of habitat.  Belize has some of the highest density of Jaguars throughout its entire range.

Jaguars are, in their own right, deserved of conservation efforts. However, with their large ranges and daily movement requirements (up to 4km in a single day), any effort to conserve habitat for jaguars will lead to extensive biodiversity preservation, with numerous species and vegetation communities protected within the cats range.

The jaguar can therefore be viewed in the basic sense as an indicator of the quality and extend of suitable habitat in any landscape. My modelling efforts use the jaguar as a case study, to promote jaguar conservation itself but also to address larger scale ecosystem function and resilience questions.

GRASS GIS

I'm now mainly working on Mac OS so using ArcGIS is becoming a bit of a problem. I have it on my Del laptop, but this is getting a bit slow now and it takes a while to do anything with the big datasets that I need to use of Belize. I also have VMWare on my iMac, but its linked to my university desktop environment, rather than being standalone and so the whole windows experience is quite a painful one.

Roll in - GRASS. An open source GIS package, find more information here.
GRASS works on any platform which makes it appear a good choice. I've yet to test its capabilities but I'll be updating my progress with it in the near future.

To get GRASS working, it requires three frameworks (GDAL Complete, Freetype and Cairo) to be installed prior to installing the GRASS package. Find them, and more info at www.kyngchaos.com/software/grass.

Some useful technical information

If the eclipse.ini file needs editing, (to increase memory or 'Java heap space') this can be found easily by going through the eclipse directory in Windows. In Mac OSX, go to eclipse.app, right-click, open package contents, contents, Mac OS, then open the eclipse.ini file in text edit.

JDK and JRE are needed for model development. The Java Runtime Environment is needed to run the java applications, the Java Development Kit is needed to develop java applications.

Subversion needs to use the SVNKit rather than the JavaHL in eclipse. This is true for Windows and Mac OS.
Subversion also brings problems when trying to save the scenario in repast. The projectName.rs folder and the styles sub folders both need to be un-checked as read-only. I've found this problem with both Windows and MacOS. In Windows, a secondary projectName.rs.bak folder is created if saving the scenario encounters this problem. In this case the subfolders and files need to be moved back into the projectName.rs folder and the projectName.rs.bak folder deleted. This doesn't seem to occur in Mac OS.

JOGL and Java3D jar files can be downloaded and installed directly from the repast homepage; http://repast.sourceforge.net/download-extras.html, again this is true for Windows and Mac OS.
Java3D files allow applications with 3D displays to run.
JOGL is Java OpenGL which is a wrapper that allows OpenGL to be used, necessary for repast models to run successfully.

Python plugin for eclipse - need to also download ActiveTcl (currently version 8.5.10 as of Sept 11) to allow use of TKinter.

GeoTools seems to be a set of java open source code library classes which provide standard compliant methods for manipulation of geospatial data. Should allow use of raster files, without converting to .pgm files. Currently testing this as of Sept 11.
There is a website dedicated to the open source files - http://geotools.org/
My current version of eclipse seems to have access to these class files without the need to download anything extra. The geoTools website seems to indicate you need to download and install the GeoTools code into both eclipse and netBeans. Will update when I know more.