Enhanced Landscape Resistance Surface: 270 m, Modoc Plateau

The Modoc Plateau's Enhanced Resistance Surface (version 6_H2b) provides an estimate of general landscape resistance to animal movement (scaled from 10 to 800) to be used in connectivity analysis. It was used to guide Linkage Mapper’s connectivity algorithms in generating least cost corridor, pinch-point, and prioritized linkage results.

This dataset was created using ESRI's ArcGIS ModelBuilder and the Conservation Biology Institute’s EEMS (Environmental Evaluation Modeling System) fuzzy logic modeling framework. Spatially-explicit logic modeling hierarchically integrates numerous and diverse datasets into composite layers, quantifying information in a continuous rather than binary fashion. This technique yields accessible decision-support products that stakeholders can use to craft scientifically-rigorous management strategies.

The connectivity resistance surface is not species-specific; rather, it represents structural connectivity, based on the condition of the landscape (the extent and type of alteration due to human activity), which impacts/presents barriers to species’ movements across the landscape.

In short, our methods were to combine two different characterizations of landscape condition, and then to fine tune this combination so the connectivity modeling algorithm more consistently responded to movement barriers. The first characterization of landscape condition used in this analysis is termed “High Contrast Landscape Intactness” (Conservation Biology Institute, 2017):  http://eemsonline.org?model=4gkfUC0B4ytq3jg8fD6QJcSSdHxKAs0A. We created this fine-scale terrestrial intactness surface using EEMS logic modeling (details in attached document). The second input dataset, termed “ Human Modification ”, was created by Conservation Science Partners (Conservation Science Partners, Inc. 2016; Theobald, 2013) and shows the degree of human modification based on stressors defined by The Human Activities Framework (Salafsky et al. 2008; http://cmp-openstandards.org/using-os/tools/threats-taxonomy/). We normalized these inputs to the same range and combined them to get an Average Landscape Resistance surface.

Initial Linkage Mapper runs of the connectivity model based on the Average Landscape Resistance yielded linkages passing through lakes and rivers. Water barriers were not getting high enough resistance values, so we burned in higher values for these features to create an “Enhanced Resistance Surface”. Thus, our landscape resistance surface is representative of winter conditions, when water bodies are full. Furthermore, contextual conditions of roads (such as road density or distance from urbanization) were causing Linkage Mapper to erroneously derive road crossings or underpasses where they do not exist on the landscape. To address this, we burned in constant values to roaded reporting units of the Enhanced Resistance Surface. Hence, all road cells of the same class have the same minimum value, and the resistance values near roaded reporting units reflect contextual values, such as road density.

Overall, our final output characterizes barriers to animal movement and the permeability of (ability for an animal to traverse) the landscape at 270 square meter resolution, based on the level and type of human disturbance present.

Results are dependent on the quality of available input data for a given area.

Please see attached document for full methodology, as well as model diagrams, & details.

Filename: Enhanced_Resistance_with_Barrier_Rds_H20_Correction_HumanModTheo_TIRS270mH2b