Landscape fragmentation fragmentation Landscape due to to transportation transportation infrastructure infrastructure due and urban development development and urban Dr. Jochen Jaeger Dr. Jochen Jaeger ETH Zurich Zurich, , Switzerland Switzerland, May 2004 , May 2004 ETH jochen.jaeger@env.ethz.ch jochen.jaeger@env.ethz.ch
Landscape in the vicinity of Singen (Baden-Wurttemberg, Germany) in 1969
Motorway intersection „Singen“ in 20 years later: 1988 1969
Baden- Wurttemberg (Jaeger et al. 2001) Black Forest How much has the degree of landscape fragmentation increased? How can the consequences be assessed?
Structure of this talk Structure of this talk � Measuring landscape fragmentation Measuring landscape fragmentation � � Effective mesh size Effective mesh size � � Time series Time series � � Use as environmental indicator Use as environmental indicator � � Effects of roads on animal populations Effects of roads on animal populations � � Road Road- -density threshold density threshold � � Suitability of fencing Suitability of fencing � � Future research Future research �
How to measure the degree of How to measure the degree of landscape fragmentation landscape fragmentation � 9 suitability criteria 9 suitability criteria � � Serious problems with existing landscape indices Serious problems with existing landscape indices � � New measure: New measure: effective mesh size effective mesh size, , m m eff � eff � Based on the probability that two randomly chosen Based on the probability that two randomly chosen � points can be connected: points can be connected: Jaeger (2000), Landscape Ecology � m m eff now available in F RAGSTATS RAGSTATS (on the www) (on the www) eff now available in F �
0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 km 2 Ortenaukreis 30.26 Spatial Spatial Emmendingen 24.61 Freudenstadt 24.60 Breisgau-Hochschw. 18.65 Rastatt 17.26 comparisons comparisons Reutlingen 15.91 Zollernalbkreis 15.48 Tübingen 14.80 Calw 14.16 Baden-Baden 13.05 Lörrach 12.17 Tuttlingen 11.61 m eff in the m eff in the Schwarzwald-Baar-Kreis 10.25 Heidenheim 10.22 Alb-Donau-Kreis 8.98 Ostalbkreis 8.87 44 rural districts 44 rural districts Waldshut 8.83 Main-Tauber-Kreis 8.69 Rottweil 8.18 in Baden- - in Baden Neckar-Odenwald-Kreis 8.09 Göppingen 7.96 Freiburg i. B., St. 7.78 Wurttemberg urttemberg W Böblingen 7.46 Karlsruhe 7.25 Esslingen 7.24 Biberach 7.13 Sigmaringen 7.11 Heilbronn 6.89 Rhein-Neckar-Kreis 6.63 Rems-Murr-Kreis 6.21 Ravensburg 6.17 Schwäbisch Hall 5.51 Enzkreis 5.42 Hohenlohekreis 5.01 Konstanz 4.96 Heidelberg, Stadt 4.62 Ludwigsburg 4.29 Bodenseekreis 3.82 Heilbronn, Stadt 2.68 Jaeger et al. (2001) Jaeger et al. (2001) Pforzheim 2.55 Karlsruhe, Stadt 2.37 Ulm 2.31 Mannheim 1.74 Stuttgart 1.63
Landscape change: Time series Landscape change: Time series m eff [km 2 ] m eff [km 2 ] Baden-Wurttemberg 12.00 P Hohenlohekreis 30 10.00 L U 8.00 K Ravensburg 20 B 6.00 Konstanz R Bodenseekreis 4.00 H 10 Ludwigsburg 2.00 Ulm Pforzheim 0.00 0 1930 1940 1950 1966 1977 1989 1920 1940 1960 1980 2000 2020 Year Year 1998 � Used as indicator (impact on biodiversity) in the Used as indicator (impact on biodiversity) in the � Environmental Report of Baden- -Wu Wurttemberg (2003) rttemberg (2003) Environmental Report of Baden
Useful for measurements easurements Useful for m and assessments assessments: : and time series series ( (environmental environmental time � � indicator) ) indicator setting environmental environmental setting � � standards standards management and and regulation regulation management � � for the the future future for Results published in: Results published in: Jaeger, J. 2002: Jaeger, J. 2002: Landschaftszerschneidung. Landschaftszerschneidung . Ulmer, Stuttgart. Ulmer, Stuttgart. (English translation in planning) (English translation in planning)
currently used in eff currently used in m eff m � 5 states of Germany: 5 states of Germany: � � Baden Baden- -Wu Wurttemberg, rttemberg, � � Hesse Hesse, , � � Bavaria, Bavaria, � � Thu Thuringia ringia, , � � Schleswig Schleswig- -Holstein. Holstein. � � Ongoing discussion about using it in all states of Ongoing discussion about using it in all states of � Germany as one of 24 core indicators of Germany as one of 24 core indicators of sustainability. sustainability. � European Environmental Agency (EEA) European Environmental Agency (EEA) � � Switzerland: Project proposal in progress Switzerland: Project proposal in progress �
Finland Collaboration Collaboration Estonia Sweden with the with the Lithuania European European Norway Latvia Environmental Environmental Albania Greece Agency (EEA) Agency (EEA) Romania M acedonia Bosnia and Herzegowina � since Nov. 2003 since Nov. 2003 � Italy Spain � 32 European 32 European � Yugoslavia countries countries United Kingdom Poland Ireland Bulgaria France Slovakia Switzerland Portugal Croatia Austria Slovenia Hugary Czech Republic Germany Jaeger et al., in prep in prep . . Jaeger et al., Luxembourg Netherlands Denmark m eff [km 2 ] Belgium 0.00 2500.00 5000.00 7500.00 10000.00
Effects of roads and railroads Effects of roads and railroads Buch Forman et al. (2003) Forman et al. (2003) Buch � Road Road Ecology Ecology: an : an � scannen hier hier scannen emerging new new and and emerging relevant discipline discipline relevant � Road Road Ecology Ecology is is � “the the sleeping sleeping giant giant of of “ conservation biology biology“ “ conservation (Forman 2002) (Forman 2002) 2003
Roads and Traffic Habitat Loss Traffic Mortality Road Avoidance R.I.P. Population Subdivision Reduced Population Size Reduced Population Persistence
Increasing road density… … Increasing road density . . . …reduces probability of population persistence: reduces probability of population persistence: … Linearly or with a threshold? Linearly or with a threshold? ?
The road road density density threshold threshold The 1 Probability of population 0.8 persistence 0.6 0.4 0.2 0 0 2 4 6 8 10 12 Number of roads Artwork thanks to Cristina Boschi. Jaeger, J., Fahrig, L., Ewald, K., in prep .
Behavior at the road Behavior at the road road avoidance = animals don = animals don’ ’t try to cross t try to cross road avoidance traffic mortality = percent of animals killed on the road = percent of animals killed on the road traffic mortality proportion of animals 100% avoiding the road 1- R R 1-K K road proportion of animals killed proportion of succeeding animals
Spatially explicit individual- - Spatially explicit individual based simulation model based simulation model road
Persistence probability 0.9 Pers. prob. 0.8 0.7 0.6 0.5 0.4 0.3 0.2 effect of a fence 0.1 0 0 0.2 0 0.4 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 traffic mortality 0.6 0.8 road avoidance 1 1
Persistence probability 0.9 Pers. prob. 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 0.2 0 0.4 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 traffic mortality 0.6 0.8 road avoidance 1 1
When do fences enhance population survival? Fence 1 0.9 Fence threshold line 0.8 road avoidance 0.7 0.6 0.5 0.4 0.3 fence reduces survival 0.2 0.1 fence enhances survival 0 0.8 0 1 0.6 0.2 0.4 Jaeger and Fahrig (2004), traffic mortality Conservation Biology
Future research questions Future research questions � Bundling of roads Bundling of roads � � Relative importance of road configuration and Relative importance of road configuration and � road length road length � Response times to new roads Response times to new roads � � Landscape connectivity Landscape connectivity � � Effect of different matrix types Effect of different matrix types � � Time series of landscape fragmentation in Time series of landscape fragmentation in � Switzerland Switzerland � Comparison with Comparison with metapopulation metapopulation models models � � Empirical data Empirical data � � Effects of overpasses and underpasses Effects of overpasses and underpasses �
Collaboration Collaboration � L. L. Fahrig Fahrig , Carleton University, Ottawa, ON, Canada , Carleton University, Ottawa, ON, Canada � � A. Clevenger A. Clevenger , Montana State Univ., USA , Montana State Univ., USA � � A. Seiler A. Seiler , Univ. of Uppsala, Sweden , Univ. of Uppsala, Sweden � � S. S. Kleeschulte Kleeschulte , EEA, Univ. , EEA, Univ. Auton Auton. de Barcelona, Spain . de Barcelona, Spain � � K. Frank K. Frank , UFZ Leipzig, Germany , UFZ Leipzig, Germany � � H. H.- -G. Schwarz G. Schwarz- -von von Raumer Raumer , Univ. of Stuttgart, Germany , Univ. of Stuttgart, Germany � � R. R. Serrouya Serrouya , , Kokanee Kokanee Forest Forest Consulting Consulting, , BC, Canada BC, Canada � � S. Alexander S. Alexander , Univ. of Calgary, AB, Canada , Univ. of Calgary, AB, Canada � � M. Percy M. Percy , Banff National Park, BC, Canada , Banff National Park, BC, Canada � � S. S. Saura Saura , Univ. de , Univ. de Lleida Lleida, Spain , Spain �
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