Background/Question/Methods In any landscape, suitable habitat occurs as an array of patches.  The more time organisms spend in these patches, the more secure (i.e., higher probability of survival) the organisms are.  Energy developments, whether fossil fuel or alternative sources, increase fragmentation, and in turn, risk to organisms.  To mitigate these impacts, tools are needed to measure changes in habitat security.

We present a new method in which landscapes are displayed as binary maps with security of individual cells based on characteristics of neighboring cells. All cells within 2-cell x 2-cell windows are reclassified as habitat if ³3 cells are habitat and as non-habitat if ≤1 cell is habitat.  Windows with 2 cells of habitat are randomly categorized as either habitat or non-habitat.  All cells within each 2x2 window are aggregated into a single cell for the next iteration.  Iterations continue until the 2x2 window covers more than half of the landscape. The measure of security for each cell in the original array is the number of iterations in which it is classified as habitat.  We explored habitat security using gradient percolation maps in which the probability of a cell being habitat (p) varied linearly along the x-axis.   We graphed the change in p as the window size increased.

Results/Conclusions We found critical values of p above which local densities increase and below which densities decrease with subsequent iterations.  These critical densities differentiated connected and unconnected landscapes.  Non-habitat cells near locally high densities of habitat cells received higher measures of security than isolated habitat cells indicating potential value as corridors.  We also compared habitat security on maps before and after disturbances.  Extent of impacts was not equal in all directions but was dependent on density and location of habitat cells.  This habitat security measure will improve the ability to predict and manage the impacts of energy development.