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A new cost‐distance model for human accessibility and an evaluation of accessibility bias in permanent vegetation plots in Great Smoky Mountains National Park, USA
Author(s) -
Jobe R. Todd,
White Peter S.
Publication year - 2009
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.1111/j.1654-1103.2009.01108.x
Subject(s) - vegetation (pathology) , national park , geography , vegetation types , environmental science , ecology , physical geography , habitat , biology , medicine , archaeology , pathology
Question: Can a new cost‐distance model help us to evaluate the potential for accessibility bias in ecological observations? How much accessibility bias is present in the vegetation monitoring plots accumulated over the last three decades in Great Smoky Mountains National Park? Location: Great Smoky Mountains National Park, North Carolina and Tennessee, USA. Methods: Distance, slope, stream crossings, and vegetation density were incorporated into a least‐cost model of energetic expenditure for human access to locations. Results: Estimated round‐trip energy costs for the park ranged from 0  to 1.62 × 10 5  J kg −1 . The estimated round‐trip energetic expenditure for the surveys ranged from 53 to 1.51 × 10 5  J kg −1 . Their distribution was more accessible than the random expectation. Ten (17%) of the vegetation types in the park are significantly under‐sampled relative to their area, and 16 (29%) are over‐sampled. Plots in 18 of the 40 vegetation types exhibited a significant positive correlation with accessibility. Conclusions: The least‐cost model is an improvement over previous attempts to quantify accessibility. The bias in plot locations suggests using a least‐cost model to test for bias in cases in which human accessibility is confounded with other sources of ecosystem variation.

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