Landscape Ecology

, Volume 20, Issue 8, pp 927–940 | Cite as

Landscape-scale Edge Effect in Predation Risk in Forest-farmland Mosaics of Central Europe

Research Article
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Abstract

Avian nest predation is known to increase with the degree of forest fragmentation. A common explanation is that farmland allows for high densities of generalist predators, and predators penetrating into the forest cause higher nest losses at forest-farmland edges than in forest interiors. In contrast to numerous patch-level studies of forest edge effects conducted earlier, we broadened the spatial extent to the landscape. We tested the hypothesis of increased predation near farmland over distances of >4 km from forest–farmland edges into forest interiors in five mountain ranges in Germany, using artificial ground nests. We considered two landscape settings: (1) Transitions between a forest matrix and a farmland matrix, and (2) farmland patches within a forest matrix. Nest losses were not significantly higher in vicinity to a farmland matrix, but proximity to a pasture within the forest matrix strongly increased predation risk. We speculate that these differences resulted from landscape geometry. Farmland patches and matrix alike are highly attractive to generalist predators, and are regularly visited by red foxes from the forest. Predators that traverse the forest and take prey along the way, will cause a concentration of predation risk towards a patch (pasture), but not towards an adjacent matrix (farming lowlands), of feeding habitat. Contrary to previous evidence that edge effects in nest predation level off after 50 m, nest fate was related to distance to pastures across the entire study extent of 4.1 km. Our results suggest that landscape context and predator mobility may greatly affect spatial predation patterns.

Keywords

Artificial nests Ecotones Experiment Fragmentation Landscape geometry Nest predation Spillover predation 
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Copyright information

© Springer 2005

Authors and Affiliations

  1. 1.Department of Wildlife Ecology and Management, College of Forest and Environmental SciencesUniversity of FreiburgFreiburgGermany
  2. 2.Wildlife Research and Management UnitTechnical University of MunichFreisingGermany
  3. 3.Stablab, Institute of StatisticsUniversity of MunichMunichGermany

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