Spatially explicit modeling of community occupancy using Markov Random Field models with imperfect observation: Mesocarnivores in Apostle Islands National Lakeshore

How species organize spatially is one of ecology’s most motivating questions. Multiple theories have been advanced and various models developed to account for the environment, interactions among species, spatial drivers. However, relative importance comparisons explanatory phenomena generally are neglected in these analyses. We a explicit community occupancy model based on Markov random fields that accounts auto-correlation interspecific while also accounting interaction detection. Simulations demonstrated can distinguish different mechanisms environmental sorting, such as competition spatial-autocorrelation. applied our camera trap data from fisher (Pekania pennanti)–marten (Martes americana) coyote (Canis latrans)-fox (Vulpes vulpes) system Apostle Island National Lakeshore (Wisconsin, USA). Model results indicated observed partitioning pattern between marten distributions could be explained best by flipped mainland–island source–sink rather than competition. For coyote–fox system, we determined that, addition pattern, there was positive association fox deserved further study. Our readily other landscapes (island non-island systems), enhancing understanding coexistence patterns.