M2BStudy/Permeability_Surface_Naturalness (ImageServer)

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Service Description: Degree of human modification and resistance surfaces for California, 2017. To model the resistance to ecological flow across California as the main input to a connectivity model (e.g., Circuitscape), we generated a resistance surface (R) modeled from the degree of human modification (H) layer. The resistance surface was calculated as: R = (H + 1.0)^10 to mute the differences between natural lands and accentuate the differences between converted lands. We did this following a sensitivity analysis of different rescaling options. To calculate the degree of human modification, we followed methods described in Theobald (2013), with adjustments to include the number of lands in highways (footprint = 30 m for each lane), as well as roads on private forested lands, and additional power line and oil/gas pipelines. We also adjusted lakes, rivers, and estuaries to the highest resistance (using rivers from USGS NHD High resolution polygon rivers). A list of stressors (or threats to natural lands) was organized based on The Human Activities Framework (Salafsky et al. 2008). At the top level, stressors are organized into five Level I classes: residential and commercial development, agriculture, energy production and mining, transportation and service corridors, and biological harvesting. These are further broken into 1-3 specific activities, resulting in 11 Level II classes. For each stressor, specific datasets were used on which to calculate a specific indicator(s). In total, nearly two-dozen datasets were used to depict 14 types of human activities. Thus, the overall degree of human modification (H) at a location is calculated as: H = I x F, where a value of 0.0 has no human modification and a value of 1.0 has high modification. This dataset was resampled using the mean value from the original 30 m resolution to 810 m. We recommend that any analysis should consider a minimum mapping unit of roughly 810 m (cell size, roughly 160 acres). This dataset was produced under a contract between The Nature Conservancy of California and Conservation Science Partners Inc. Analysis and spatial data produced by Conservation Science Partners Inc. 2017. Truckee, CA, USA. This work is licensed under a Creative Commons Attribution 3.0 License.

Name: M2BStudy/Permeability_Surface_Naturalness

Description: Degree of human modification and resistance surfaces for California, 2017. To model the resistance to ecological flow across California as the main input to a connectivity model (e.g., Circuitscape), we generated a resistance surface (R) modeled from the degree of human modification (H) layer. The resistance surface was calculated as: R = (H + 1.0)^10 to mute the differences between natural lands and accentuate the differences between converted lands. We did this following a sensitivity analysis of different rescaling options. To calculate the degree of human modification, we followed methods described in Theobald (2013), with adjustments to include the number of lands in highways (footprint = 30 m for each lane), as well as roads on private forested lands, and additional power line and oil/gas pipelines. We also adjusted lakes, rivers, and estuaries to the highest resistance (using rivers from USGS NHD High resolution polygon rivers). A list of stressors (or threats to natural lands) was organized based on The Human Activities Framework (Salafsky et al. 2008). At the top level, stressors are organized into five Level I classes: residential and commercial development, agriculture, energy production and mining, transportation and service corridors, and biological harvesting. These are further broken into 1-3 specific activities, resulting in 11 Level II classes. For each stressor, specific datasets were used on which to calculate a specific indicator(s). In total, nearly two-dozen datasets were used to depict 14 types of human activities. Thus, the overall degree of human modification (H) at a location is calculated as: H = I x F, where a value of 0.0 has no human modification and a value of 1.0 has high modification. This dataset was resampled using the mean value from the original 30 m resolution to 810 m. We recommend that any analysis should consider a minimum mapping unit of roughly 810 m (cell size, roughly 160 acres). This dataset was produced under a contract between The Nature Conservancy of California and Conservation Science Partners Inc. Analysis and spatial data produced by Conservation Science Partners Inc. 2017. Truckee, CA, USA. This work is licensed under a Creative Commons Attribution 3.0 License.

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Copyright Text: This dataset was produced under a contract between The Nature Conservancy of California and Conservation Science Partners Inc. Analysis and spatial data produced by Conservation Science Partners Inc. 2017, Truckee, CA, USA. The Mayacamas to Berryessa (M2B) Connectivity Network is a project funded by the California Landscape Conservation Partnership to Pepperwood Foundation. Key contributors include Morgan Gray, Adina Merenlender, Lisa Micheli, and the M2B steering committee. Citation: Gray M., L. Micheli, A.M. Merenlender. 2018. Methodology for building habitat connectivity for climate adaptation: Mayacamas to Berryessa Connectivity Network (M2B). A technical report by the Dwight Center for Conservation Science at Pepperwood, Santa Rosa CA. 51 pp. References: Bonham-Carter G. 1994. Geographic Information Systems for geoscientists. Elsevier, 398 pgs. Brown MT, Vivas MB. 2005. Landscape development intensity index. Environmental monitoring and assessment 101:289-309. Salafsky N, et al. 2008. A standard lexicon for biodiversity conservation: unified classifications of threats and actions. Conservation Biology 22(4):897-911. Theobald DM. 2013. A general model to quantify ecological integrity for landscape assessments and US application. Landscape Ecology 28(10):1859-1874. Use constraints: This work is licensed under a Creative Commons Attribution 3.0 License. No warranty is made by Data Basin for use of this dataset.

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