Modeling habitat patches with GIS

A habitat patch is a cluster of pixels that are good enough, big enough, and close enough together to support breeding by a particular species. In corridor modeling, patches are useful as start and end points for corridors, as steppingstones in the matrix, and as descriptors to evaluate utility of a linkage design for each focal species. In a GIS context, modeling patches requires you to set:

  • A moving window size that reflects perceptual range and landscape effects on habitat quality
  • A minimum threshold of habitat quality required for breeding
  • A minimum area to support breeding

What is a habitat patch?

A habitat patch is a cluster of pixels that are good enough, big enough, and close enough together to support breeding by a particular species. “Good enough” means that they have sufficient resources for the animal. “Big enough” reflects the fact that there needs to be enough area to support at least one breeding unit, typically considered a mating pair of animals with overlapping home ranges. “Close enough together” means that the pixels must be clustered, rather than divided into a checkerboard by too much interspersion with pixels of bad habitat. “By a particular species” emphasizes the fact that one species' breeding patch may be another species' worst nightmare.

Why are patches useful for corridor modeling?

You can design a linkage without delineating habitat patches. In fact, most corridor designs do not incorporate patch models. But in our experience, modeling patches of breeding habitat is useful in three ways:

How to model and map patches

To delineate habitat patches, you must specify the threshold habitat quality for breeding, and the minimum area of suitable habitat necessary to sustain a breeding pair or population. This is easily done in a GIS, and in CorridorDesigner, by counting pixels that exceed the threshold value and that can touch at an edge or corner. However, two problems sometimes arise with this procedure in this simple form:

The procedure could fail to recognize some patches usable by an animal with a large home range. Such animals would probably “ignore” a narrow ribbon of non-habitat imbedded in otherwise suitable pixels. However, if that narrow ribbon divides the suitable pixels into two clusters, each slightly below the minimum size, this procedure would not recognize the habitat patch.

Conversely, this procedure could recognize some habitat patches that an animal would probably not use. The extreme example would be a diagonal string of pixels touching only at their corners, surrounded by pixels of very low habitat suitability. In this case, edge effects such as predators, nest parasites, or exotic species might make this area unsuitable for breeding, despite its being identified as a “patch.”

Neighborhood effects

CorridorDesigner gives you an option to address both of these problems by computing the average habitat suitability score of all pixels within a moving window around the focal pixel and using this “neighborhood habitat suitability score” to define patches. In corridor designer we use the neighborhood score only to define patches; each pixel retains its raw score in all other procedures.

Because appropriate, species-specific data are usually lacking, it is difficult to determine the optimal neighborhood size for a species. Estimates of home range size, daily spatial requirements, and the relationship between body mass and spatial requirements may all be useful in determining an ecological neighborhood. In our modeling, we used one of three moving window sizes, namely a 200-m radius, a 3x3-pixel square, and none, depending on our understanding of the biology of the species.

Threshold habitat quality

Whether you use raw habitat suitability scores or the habitat suitability in a moving window, you must specify the cutoff between breeding and non-breeding habitat. In some of our early designs, we used an arbitrary habitat suitability scale, and we designated the top 40% of the pixels as potential breeding habitat. This was obviously unsatisfactory: a species might find 100% of one landscape is suitable for breeding, and 0% of another landscape. An arbitrary 40% does not make biological sense. So we switched to a scheme in which habitat suitability scores had a biological meaning, as illustrated below.

Biological interpretation of habitat suitability scores

  • 100 = best habitat, highest survival and reproductive success
  • 80 = lowest score typically associated with successful breeding
  • 60 = lowest score associated with consistent use and breeding
  • 30 = lowest value associated with occasional use for non-breeding activities
  • All values less than 30 = avoided
  • 0 = absolute non-habitat

Assigning meaning to the scores made it much easier to assign a threshold (60 in this example). Of course, for this to work, you must parameterize habitat models explicitly keeping this framework in mind, instead of applying this framework after having already parameterized a model.

Minimum patch size

It is useful to map at least one patch size: the area sufficiently large enough to support a breeding event (usually a home range). We recommend also defining a larger habitat patch size capable of supporting a larger population of individuals. We mapped patches in two size classes, namely:

  • Population patch: an area large enough to support breeding for 10 years or more, even if the patch were isolated from interaction with other populations of the species. When population-wide data were not available, we often assumed that a habitat patch five times larger than a breeding patch would sufficiently support breeding for 10 or more years.
  • Breeding patch: An area smaller than a population patch, but large enough to at least occasionally support a single breeding event. For example, this might be an area large enough to support a single breeding pair through courtship and rearing of young to dispersal age.