Modeling landscape condition for biodiversity assessment—Application in temperate North America
2017
Hak, John C. | Comer, Patrick J.
Conservation decisions are well supported by predictive spatial models that indicate the relative ecological condition of a given place. The intent of this 90m pixel landscape condition model is to use nationally available spatial data from the USA, Mexico, and Canada to express assumptions regarding the relative ecological effects of land uses on terrestrial natural communities and species. This approach emphasizes and updateable and transparent design which takes advantage of empirical biodiversity data from the USA to both calibrate and validate the model. Map layers depicting infrastructure, land use, and modified vegetation were each scored for site impact and distance decay, and then combined into one map surface. Field observations from Natural Heritage Programs, each scored for relative ecological condition (in categories A=excellent to D=poor), were used to calibrate distance decay parameters. Some 90,000 observations for at-risk species, invasive plant species, and natural communities were used for model validation. Statistically significant distinctions in ecological condition among validation samples were predicted by the resultant spatial model. Variation in landscape condition was then summarized by regional U.S. Landscape Conservation Cooperatives (LCCs) in terms of areas approximating A–D condition. Montane and desert LCCs scored on average much higher in area approximating “A” and “B” landscape condition, while LCCs with more substantial agricultural and urban footprints scored overwhelmingly within the “D” range of condition. Similar analyses illustrated range-wide scoring of landscape condition for major vegetation types across temperate North America.
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