The Rauischholzhausen agenda for road ecology

• Published in: Ecology and society 2007, Vol.12 (1), p.11, Article art11
• Main Authors: 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
• Format: Article
• Language: English
• Subjects: before-after design; before-after-control-impact design; biodiversity; breeding bird populations; conservation; Conservation biology; control-impact design; decision making; deer; density; Ecology; environmental impacts; experimental design; extrapolation; habitat; hierarchy of study designs; Highway engineering; Human ecology; inferential strength; Insight; Landscape ecology; landscape scale; Landscapes; methodological standard; mitigation; Mortality; Population ecology; population persistence; precautionary principle; research agenda; road ecology; road effects; road networks; Roads; sampling design; swareflex reflectors; uncertainty; weight of evidence; Wildlife ecology
• ISSN: 1708-3087; 1708-3087
• DOI: 10.5751/ES-02011-120111

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.