Comparison of patch-based and synoptic connectivity algorithms with graph theory metrics. A case study in Reggio Calabria metropolitan area (South Italy)

Context: Predicting and mapping connectivity between habitats and populations is critical to addressing habitat loss and biodiversity issues. Several strategies in the literature exist to understand, restore, and preserve ecological connectivity. The main issue of the current research is to identify which connectivity modeling strategies are the most reliable for planning purposes. Objectives: Our goals in this paper were to compare connectivity predictions using a wide variety of commonly used approaches to improve the understanding of the similarities and differences in the predictions of these methods. Specifically, we investigated the differences in connectivity predictions related to the connectivity algorithm, the number and distribution of source points, and the threshold distance at which connectivity is allowed between locations. First, we separately applied different strategies and methods commonly used in the literature to model connectivity in the same study area. Then, going through a series of hypotheses, we compared the different models to confirm or disprove the initial hypotheses. Methods: We proposed 4 main hypotheses and 14 combinations of them, hypothesizing that what most influences the results of connectivity models are different dispersal distance thresholds; differences in connectivity algorithms, especially kernel, path, and graph theory-based approaches; differences in predictions produced by two different software tools, UNICOR and Graphab; use of source points derived from a synoptic or patch-based perspective. Results: We found that the dominant pattern of differences in the predictions of different connectivity analyses was related to the method of analysis, with clear differences between kernel, path, and graph-theory approaches and relatively little effect due to the density and distribution of source points or the distance threshold used to define dispersal capability. Conclusions: This work provides one of the first comparisons of spatial predictions of different methods, frameworks, and parameterizations of connectivity models. Our results support environmental planning by clarifying what most influences predictions of movement patterns and how the predicted connectivity networks differ between different analytical frameworks.