Identifying Ecotone Location Using The Co-Occurrence Property

Questions Spatial characteristics of ecotones can affect ecotone function and define their role in ecological systems. Identifying ecotone location is necessary to quantify the relationship between spatial characteristics and function, yet there is no standard approach, particularly for compositionally complex ecotones where binary classification for the two adjacent systems is difficult to assign. We tested a new approach for identifying ecotone location based on the co-occurrence property, which recognizes ecotones as areas where species from adjacent systems co-occur. We assessed whether the approach can objectively identify the location of the Tension Zone in Wisconsin. Location Wisconsin, USA. Methods Ecotone Co-occurrence Mapping (ECoMap) is a multi-step approach: (a) indicator species analysis identifies representative species of two adjacent systems; (b) a ratio map constructed from the spatial densities of the indicator species identifies high co-occurrence areas; and (c) contour lines encapsulate highest co-occurrence areas. We applied this approach to identify the Tension Zone location using point locations of witness trees from the mid-1800s Public Land Survey. We assessed the approach by examining results of multiple permutations, testing sensitivity to different initial boundary configurations, and comparing it to a subjectively derived map, the Curtis Tension Zone. Results The location of the Tension Zone was identified consistently in multiple permutations, though there is minor variability in certainty of final ecotone location. Ecotone width varied substantially along the Tension Zone. The location was similar to the Curtis Tension Zone but slightly farther north and more spatially detailed. Sensitivity to initial boundary configuration was low. Conclusions The ECoMap approach was robust and identified a spatially detailed Tension Zone location. This approach is broadly applicable and can be used to identify the location of simple or compositionally complex ecotones where spatial data of species occurrences and modest prior knowledge of general boundary location are available.