DotDotGoose is a free, open source tool to assist with manually counting objects in images. DotDotGoose was purpose-built since most conservation researchers and practitioners working on counting objects in images were using software such as Adobe Photoshop and ImageJ which are not ideally suited for many conservation applications.

The DotDotGoose interface makes it easy to create and edit classes of objects to be counted and you can pan and zoom to accurately place points to identify individual objects. Information about objects can be stored in custom fields and this metadata can be exported for use in spreadsheet or statistics software.

Maxent is a software package for modeling species niches and distributions by applying a machine-learning technique called maximum entropy modeling. From a set of environmental (e.g., climatic) grids and georeferenced occurrence localities, the model expresses a probability distribution where each grid cell has a predicted suitability of conditions for the species. Under particular assumptions about the input data and biological sampling efforts that led to occurrence records, the output can be interpreted as predicted probability of presence (cloglog transform), or as predicted local abundance (raw exponential output).

The idea for Maxent was first conceived of here at the Center for Biodiversity and Conservation at the American Museum of Natural History (AMNH) through a public-private partnership between the AMNH and AT&T-Research. Steven Phillips and the other developers of Maxent are still engaged in its development and maintenance, and the Google group will remain the main mechanism for user questions. Much additional information can be found in the Google group, software tutorials, and other resources on the project page.