Evaluating the effectiveness of road mitigation measures
Grift, E.A. van der; Ree, R. van; Fahrig, L. ; Houlahan, J.E. ; Jaeger, J.A.G. ; Klar, N. ; Francisco Madriñan, L. ; Olson, L. - \ 2013
Biodiversity and Conservation 22 (2013)2. - ISSN 0960-3115 - p. 425 - 448.
non-wildlife passages - banff-national-park - high-speed railway - frog rana-arvalis - large mammals - gene flow - habitat fragmentation - southern california - crossing structures - bird populations
The last 20 years have seen a dramatic increase in efforts to mitigate the negative effects of roads and traffic on wildlife, including fencing to prevent wildlife-vehicle collisions and wildlife crossing structures to facilitate landscape connectivity. While not necessarily explicitly articulated, the fundamental drivers behind road mitigation are human safety, animal welfare, and/or wildlife conservation. Concomitant with the increased effort to mitigate has been a focus on evaluating road mitigation. So far, research has mainly focussed on assessing the use of wildlife crossing structures, demonstrating that a broad range of species use them. However, this research has done little to address the question of the effectiveness of crossing structures, because use of a wildlife crossing structure does not necessarily equate to its effectiveness. The paucity of studies directly examining the effectiveness of crossing structures is exacerbated by the fact that such studies are often poorly designed, which limits the level of inference that can be made. Without well performed evaluations of the effectiveness of road mitigation measures, we may endanger the viability of wildlife populations and inefficiently use financial resources by installing structures that are not as effective as we think they are. In this paper we outline the essential elements of a good experimental design for such assessments and prioritize the parameters to be measured. The framework we propose will facilitate collaboration between road agencies and scientists to undertake research programs that fully evaluate effectiveness of road mitigation measures. We discuss the added value of road mitigation evaluations for policy makers and transportation agencies and provide recommendations on how to incorporate such evaluations in road planning practices.
The Rauischholzhausen agenda for road ecology
Roedenbeck, I.A. ; Fahrig, L. ; Findlay, C.S. ; Houlahan, J.E. ; Jaeger, J.A.G. ; Klar, N. ; Kramer-Schadt, S. ; Grift, E.A. van der - \ 2007
Ecology and Society 12 (2007)1. - ISSN 1708-3087 - 21 p.
breeding bird populations - precautionary principle - environmental impacts - swareflex reflectors - sampling design - habitat - conservation - density - deer - biodiversity
Despite the documented negative effects of roads on wildlife, ecological research on road effects has had comparatively little influence on road planning decisions. We argue that road research would have a larger impact if researchers carefully considered the relevance of the research questions addressed and the inferential strength of the studies undertaken. At a workshop at the German castle of Rauischholzhausen we identified five particularly relevant questions, which we suggest provide the framework for a research agenda for road ecology: (1) Under what circumstances do roads affect population persistence? (2) What is the relative importance of road effects vs. other effects on population persistence? (3) Under what circumstances can road effects be mitigated? (4) What is the relative importance of the different mechanisms by which roads affect population persistence? (5) Under what circumstances do road networks affect population persistence at the landscape scale? We recommend experimental designs that maximize inferential strength, given existing constraints, and we provide hypothetical examples of such experiments for each of the five research questions. In general, manipulative experiments have higher inferential strength than do nonmanipulative experiments, and full before-after-control-impact designs are preferable to before-after or control-impact designs. Finally, we argue that both scientists and planners must be aware of the limits to inferential strength that exist for a given research question in a given situation. In particular, when the maximum inferential strength of any feasible design is low, decision makers must not demand stronger evidence before incorporating research results into the planning process, even though the level of uncertainty may be high