https://trid.trb.org/ en-us Copyright © 2026. National Academy of Sciences. All rights reserved. http://blogs.law.harvard.edu/tech/rss tris-trb@nas.edu (Bill McLeod) tris-trb@nas.edu (Bill McLeod) https://trid.trb.org/Images/PageHeader-wTitle.jpg https://trid.trb.org/ https://trid.trb.org/View/1516583 Tue, 03 Jul 2018 17:41:02 GMT https://trid.trb.org/View/1516583 https://trid.trb.org/View/1515581 Mon, 18 Jun 2018 12:26:52 GMT https://trid.trb.org/View/1515581 https://trid.trb.org/View/1483161 Tue, 03 Oct 2017 17:30:10 GMT https://trid.trb.org/View/1483161 https://trid.trb.org/View/1483616 Tue, 03 Oct 2017 17:30:10 GMT https://trid.trb.org/View/1483616 https://trid.trb.org/View/1483617 Tue, 03 Oct 2017 17:30:09 GMT https://trid.trb.org/View/1483617 https://trid.trb.org/View/1436194 Mon, 05 Dec 2016 15:41:45 GMT https://trid.trb.org/View/1436194 https://trid.trb.org/View/1344337 Tue, 31 Mar 2015 09:07:28 GMT https://trid.trb.org/View/1344337 https://trid.trb.org/View/1346361 500 animals with GPS collars providing >2,000,000 locations to determine crossing structure and fence placement, during-construction wildlife behavior, and post-construction responses for elk (Cervus elaphus), mule deer (Odocoileus hemionus), white-tailed deer (Odocoileus virginianus), American pronghorn (Antilocapra americana), desert bighorn sheep (Ovis Canadensis ), and desert tortoise (Gopherus agassizii). Wildlife-vehicle collision (WVC) data is also useful for identifying crossing structure locations; however, this method cannot be used for species that avoid crossing roads. For example, declining populations of pronghorn are bisected by US highway 89, but no WVC data exists here for this species (Dodd et al. 2009). Therefore, the authors are using GPS data exclusively to determine where pronghorn approach the highway hopefully indicating where they may use yet to be constructed wildlife crossing structures. To date, the authors have collected >120,000 GPS locations (taken every two hours) to recommend crossing structure placement for this project. A similar “data-driven” approach was used along US 93 to provide recommendations for placement of three desert bighorn sheep overpasses to be completed in 2010 (McKinneyand Smith 2007). WVC data obviously is absent in areas where roadways did not exist, such as realignments or new highways. Therefore, along the proposed US 95 realignment, AGFD is studying pre-construction desert tortoise movements to determine crossing structure placements sufficient to allow tortoise safety and permeability once the highway is built. Although reduction of WVCs is an important measure, WVC reduction alone does not tell the whole story. Promoting wildlife permeability is also important. For instance, along an 8-km stretch of State Route 260, where crossing structure frequencies were 1.1 structure/km, Dodd et al. (2007a) documented a >80% reduction in elk-vehicle collisions following the implementation of funnel fencing linking crossing structures. Here, GPS passage rates showed that permeability did not change following upgrade of the highway. In contrast, elsewhere on SR 260, where crossing structure were spaced 2.4 km apart, WVCs were reduced by >95% following fencing connecting crossing structures. However, permeability dropped by 70%; so although WVC rates declined, the overall effect could not be determined by WVC alone. Pre- and post-construction GPS movement data are needed to show changes in permeability following reconstruction of highways. The authors provide methods and various examples of the use of GPS movement data in Arizona so that highway and wildlife managers alike may be able to use this technology in planning and monitoring their own wildlife-friendly highway projects.]]> Tue, 31 Mar 2015 09:06:34 GMT https://trid.trb.org/View/1346361 https://trid.trb.org/View/1343057 Thu, 26 Feb 2015 10:03:48 GMT https://trid.trb.org/View/1343057 https://trid.trb.org/View/1123389 2.1-m tall and 1.2-m woven-wire fences with a top-mounted outrigger were most effective. The authors studied movements of free-ranging deer before and after construction of 1.6-km of 2.4-m woven-wire and 1.6-km of 1.2-m woven-wire with a top-mounted outrigger. Fencing did not affect deer home range size, and deer often circumvented fence ends. Daily deer movements in response to fencing were reduced by 98% and 90% for the 2.4-m and outrigger designs, respectively. The outrigger design has potential for reducing collisions because of its relative affordability and ability to function as a 1-way barrier. To further test deer vision, as related to deterrents to roadway crossing, the authors developed an automated system for training deer to associate a white-light stimulus with a food reward. Each of six captive deer correctly identified the positive reward in >75% of trials by Day 19. This system will be used to further characterize the visual thresholds of deer, and to test innovative roadside mitigation strategies.]]> Thu, 01 Dec 2011 07:58:44 GMT https://trid.trb.org/View/1123389 https://trid.trb.org/View/1117568 Fri, 30 Sep 2011 16:13:05 GMT https://trid.trb.org/View/1117568 https://trid.trb.org/View/1113073 Thu, 18 Aug 2011 16:07:37 GMT https://trid.trb.org/View/1113073 https://trid.trb.org/View/1103210 Wed, 22 Jun 2011 07:58:19 GMT https://trid.trb.org/View/1103210 https://trid.trb.org/View/1099045 Fri, 15 Apr 2011 12:16:13 GMT https://trid.trb.org/View/1099045 https://trid.trb.org/View/1086134 Fri, 14 Jan 2011 10:20:19 GMT https://trid.trb.org/View/1086134