English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Henderson, Jan A.; Lesher, Robin D.; Peter, David H.; Ringo, Chris D. 2011. A landscape model for predicting potential natural vegetation of the Olympic Peninsula USA using boundary equations and newly developed environmental variables. Gen. Tech. Rep. PNW-GTR-841. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 35 p. A gradient-analysis-based model and grid-based map are presented that use the potential vegetation zone as the object of the model. Several new variables are presented that describe the environmental gradients of the landscape at different scales. Boundary algorithms are conceptualized, and then defined, that describe the environmental boundaries between vegetation zones on the Olympic Peninsula, Washington, USA. The model accurately predicted the vegetation zone for 76.4 percent of the 1,497 ecoplots used to build the model. Independent plot sets used to validate the model had an accuracy of 82.1 percent on national forest land, and 71.8 percent on non-national-forest land. This study demonstrated that a model based on boundary algorithms can be an alternative to regression-based models for predicting landscape vegetation patterns. Potential applications of the model and use of the environmental gradients to address ecological questions and resource management issues are presented.

A landscape model for predicting potential natural vegetation of the Olympic Peninsula USA using boundary equations and newly developed environmental variables.