4.7 Article

Learning from the past to predict the future: using archaeological findings and GPS data to quantify reindeer sensitivity to anthropogenic disturbance in Norway

期刊

LANDSCAPE ECOLOGY
卷 28, 期 5, 页码 847-859

出版社

SPRINGER
DOI: 10.1007/s10980-012-9793-5

关键词

Landscape connectivity; Historic ecology; Anthropogenic disturbance; Migration corridors; Infrastructures; Roads; Dams; Cabins; Power lines; Cumulative effects

资金

  1. Norwegian Directorate for nature management
  2. Norwegian Research Council under the program Norwegian environmental research

向作者/读者索取更多资源

Norwegian wild reindeer Rangifer tarandus tarandus are divided into 23 virtually isolated populations, primarily due to the abandonment of traditional migration and movement corridors caused by the development of infrastructures. By conducting a nation-wide, interdisciplinary pre-post study on a temporal scale spanning centuries, we modelled current reindeer movements with respect to archaeological findings to quantify long-term changes in area use related to anthropogenic disturbance. The location of 3,113 pitfall traps and hunting blinds, built 600-2000 years ago and used until 350-400 years ago, testified the location of traditional movement corridors. Current movement routes were delineated using Brownian Bridge Movement Models based on 147 reindeer GPS-monitored during 10 years. Using Path Analysis we quantified direct, indirect and total effects of different infrastructures within multiple scales (1, 5, and 10 km-radius buffers) on the current probability of use of ancient movement corridors. Tourist cabins and roads had the strongest long-term direct effects at most scales: 1 tourist cabin and 1 km road within a 1 km-radius buffer would lead, respectively, to complete area abandonment, and to a 46 % decrease in the probability of use. Power lines and private cabins had significant indirect effects on area use through their effect on roads, while hiking trails and, in particular, hydroelectric dams had highly variable effects, not significant at a nation-wide scale. Finally, we provide a flexible tool to estimate the potential long-term direct and cumulative effects of different types of infrastructures at the desired spatial scale to be used for the development of future sustainable land management plans.

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