A method for surveying the condition of extensive walking track systems

Hawes, Martin; Candy, Steve; Dixon, Grant

doi:10.1016/j.landurbplan.2005.10.001

Cited by 22 publications

(10 citation statements)

References 13 publications

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“…Trail width investigations have employed differing methods for assessing trail width: some assessed trail and tread widths as defined here, others applied variations or failed to clarify what they measured (Bayfield, 1973;Lance et al, 1989;Hawes et al, 2006;Törn et al, 2009). These differences and omissions of assessment methods have produced data that are often not comparable between studies.…”

Section: Literature Reviewmentioning

confidence: 99%

The influence of use, environmental and managerial factors on the width of recreational trails

Wimpey

Marion

2010

Journal of Environmental Management

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Section: Literature Reviewmentioning

confidence: 99%

The influence of use, environmental and managerial factors on the width of recreational trails

Wimpey

Marion

2010

Journal of Environmental Management

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“…A technique of sampling at 20 m intervals can be used to assess typically 5-7 km of track per day in remote areas (Hawes et al, 2006). Our experiences confirmed time consumption so there will be fair discussion about practicality to repeat these measurements as a part of a potential monitoring program.…”

Section: Decision Treesmentioning

confidence: 54%

“…To date, large amounts of research are focused on the impact of visitors on soil and vegetation including monitoring and modeling (Dixon et al, 2004;Farell and Marion, 2001;Monti and MacKintosh, 1979;Godefroid and Koedam, 2004;Özcan et al, 2013). A variety of efficient methods for evaluating trails and their resource conditions, especially in sensitive and vulnerable areas (alpine environment), have been developed and described in the literature (Jewell and Hammitt, 2000;Hawes et al, 2006;Ólafsdótirr and Runnström, 2013;Tomczyk and Ewertowski, 2011;Brevik and Fenton, 2012). A review by Marion and Leung (2001) concluded that the point sampling method provides accurate and precise measures of trail characteristics that are continuous or frequent (e.g., tread width).…”

Section: Introduction and Problem Overviewmentioning

confidence: 99%

Trail impact monitoring in Rocky Mountain National Park, USA

et al. 2016

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Abstract. This paper examines impacts of increased visitation leading to human trampling of vegetation and soil along several trails in Rocky Mountain National Park (RMNP) to understand how abiotic factors and level of use can influence trail conditions. RMNP is one of the most visited national parks in the USA, with 3.3 million visitors in 2012 across 1075 km 2 and 571 km of hiking trails. 95 % of the park is designated wilderness, making the balance between preservation and visitor use challenging. This research involves the application of trail condition assessments to 56 km of trails to determine prevailing factors and what, if any, connection between them exist. The study looked at a variety of inventory and impact indicators and standards to determine their importance and to develop a baseline condition of trails. The data can be used for future comparison and evaluation of development trends. We found that trail widening (mean trail width 88.9 cm) and soil loss (cross-sectional area 172.7 cm 2 ) are the most visible effects of trail degradation. Further statistical analyses of data identified the role and influence of various factors (e.g., use level and topography). Insights into the influence of these factors can lead to the selection of appropriate management measures to avoid or minimize negative consequences from increased visitation.

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“…A distance-based sampling technique involved recording categorical measurements of various impact parameters (the same as those developed for the clustered-transect technique; see Section 4.2) at regular spatial intervals along a track, and calculating the proportion of track subject to specified categorical ranges of impact value (Hawes, Candy & Dixon, 2006). The method is designed to characterise track condition over extended sections (i.e.…”

Section: Distance Samplingmentioning

confidence: 99%