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Vulnerability of moose and roe deer to wolf predation in Scandinavia- does habitat matter? International Master Programme Applied Biology, 2007 By: Lisette.

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Presentation on theme: "Vulnerability of moose and roe deer to wolf predation in Scandinavia- does habitat matter? International Master Programme Applied Biology, 2007 By: Lisette."— Presentation transcript:

1 Vulnerability of moose and roe deer to wolf predation in Scandinavia- does habitat matter? International Master Programme Applied Biology, 2007 By: Lisette Fritzon

2 Ungulates important prey for wolves Threat against wolf recovery Dramatic growth of prey populations Important species, both for hunters and for forestry production Need for more knowledge of how habitat and spatial factors may affect the vulnerability of prey Introduction

3 Examine if there are high-risk areas for moose and roe deer in a wolf territory Null hypotheses; habitat and spatial variables at kill sites did not differ when compared to control and random sites Aim

4 Moose (n=177) Roe deer (n=76) Habitat and spatial features compared 11 territories in Sweden and Norway Field work, Narrow scale Arc View, Broader scale Method

5 Territory number TerritoryNo. MooseNo. Roe deer 1Djurskog375 2Forshyttan102 3Glaskogen63 4Halgån190 5Hasselfors1636 6Jangen142 7Stadra416 8Tyngsjö243 9Ulriksberg96 10Uttersberg233 11Nyskoga150 Total17776

6 Study area showing the 11 wolf territories on the Scandinavian Peninsula.

7 Field Reconnaissance Summer 2006 253 kill sites 253 control sites Summer and winter 27 variables analysed

8 Field Reconnaissance 1. Visibility 2.Slope 3. Habitat class 4. Forest class 5. Distance to the nearest edge 6. Forest age 7. Stem diameter 8. Height of undergrowth 9. Height of forest 10. Distance to nearest largest stem 11. Number of stems 24 variables

9 30 m 500 m Kill site Control site Habitat and landscape variables were recorded 253 kill sites and 253 control sites Random direction

10 Coordinates from carcass and control points (total 506) Wolf home ranges, minimum convex polygon (MCP) method Random points (total 253), compared with kill, control Two buffer zones added, 250 meter and 1000 meter buffer 24 variables analysed Geographic Information System spatial analysis

11 Object variables (Buffer 250, 1000) Building (N), a Building (N), b Road (m), a Small road (m), a Area variables (Buffer 250, 1000) Antrophogenic area Deciduous forest Coniferous forest Clearcut Young forest Wetland Water Distance variables Distance small road (m) Distance building (m Topographic variables Slope Meters above sea level (m) Density variables (Buffer 250) Relative moose density

12 Statistical analyse Logistic Regression Field Data Moose summer vs control Roe deer vs control Logistic Regression GIS Data Moose summer vs random Roe deer vs random

13 TestVariableHigherLowerPercentage correct Significance Moose kill vs contol Height of undergrowth X 60.50.002 Proportion of meadow X 60.90.05 Average stem diameter X 61.90.030 Proportion of spruce X61.30.033 Field data

14 TestVariableHigherLowerPercentage correct Significance Roe deer vs control Number of stems X 60.50.004 Field data

15 TestVariableHigherLowerPercentage correct Significance Moose kill vs random Number of buildings (b) X62.60.005 Meter above sea level X65.20.032 Proportion clear- cuts (a) X66.00.027 GIS Data

16 TestVariableHigherLowerPercentage correct Significance Roe deer vs random Proportion coniferous forest (b) X58.60.002 Average meters above sea level X61.20.021 GIS Data

17 Discussion Habitat and spatial variables differs between kill, control and random Ungulates have a variety of anti-predator strategies High predation risks in open areas (Kunkel & Pletcher 2000) In this study,moose seems to choose more open areas, both for field data and for GIS data Same pattern as for many other studies (Seip 1992; Singer & Mack 1999; Dussault et al 2005)

18 Discussion GIS data; Roe deer avoid open areas  proportion coniferous forests higher GIS data; Moose open areas Roe deer same pattern as moose for elevation Field data; Roe deer avoid open areas  number of stems higher Field data; Moose more open areas Studies linked predation risk to landscape attributes

19 Summer and winter Chasing distance Important management and conservation implications Better predicting impacts of wolves on prey Discussion

20 Conclusion Patterns in which habitats moose and roe deer are being killed by wolves Habitat does matter Moose tendency seek open areas Roe deer tendency avoid open areas

21 Acknowledgements Håkan Sand, Camilla Wikenros, Mats Amundin, Sabrina Muller, Undine Knappwost, Grzegorz Miskulisnki, Lasse Jäderberg, Johan Jakobsson and Sam. Thank you all for making this thesis possible!

22 Thank You For Listening! Questions?

23 More studies are needed GPS radio collars on both wolves and moose/roe deer that record their locations at intervals over two winters and summers The aim would be to test whether moose/roe deer locations differs on days when wolves are present or absent With this test the advantage is that the movements of wolves can be used to test the behavioural responses by resident moose/roe deer Further research

24 Anthropogenic rea; Buffer 250m and 1000m (2) Discontinuous urban fabric with more than 200 inhabitants with minor areas of gardens and greenery (3) Discontinuous urban fabric with more than 200 inhabitants with major areas of gardens and greenery (4) Discontinuous urban fabric with less than 200 inhabitants (5) Solitary houses with property (6) Industrial or commercial units, public services and military installations (10) Sand and gravel pits 14) Green urban areas (15) Sport grounds, shooting ranges, motor, horse and dog racing tracks (17) Ski slopes (18) Golf courses (19) Non-urban parks (20) Camping sites and holiday cottage sites (30) Arable land (32) Pastures

25 Deciduous forest; Definition: Tree-covered areas consisting of a total crown cover of >30%, whereof >75% of the crown cover is made up of broad-leaved trees. Tree height is >5 meters Buffer 250m and 1000m (40) Broad-leaved forest not on mires (41) Broad-leaved forest on mires (48) Mixed forest not on mires (49) Mixed forest on mires (50) Mixed forest on open bedrock Coniferous forest; Definition: Areas consisting of trees with a total crown cover of >30%, whereof >75% of the crown cover is made up of coniferous trees. Tree height is >5 meters Buffer 250m and 1000m (43) Coniferous forest on lichen-dominated areas (44) Coniferous forest 5-15 m (45) Coniferous forest >15 m (46) Coniferous forest on mires (47) Coniferous forest on open bedrock

26 Clear-cut; Definition: Open and re-growing clear-felled areas where trees/bushes have a rough height of <2 meters. Buffer 250m and 1000m (54) Clear-felled areas Young forest; Definition: Bushes with a total cover of >30% and a height between ca. 1 and 5 meters and younger forest with a cover of >30% and a height between roughly 2 and 5 meters. Buffer 250m and 1000m (53) Thickets (55) Younger forest Wetland; Buffer 250m and 1000m (70) Inland marshes (71) Wet mires (72) Other mires Water; Buffer 250m and 1000m (80) Water courses (81) Lakes and ponds, open surface (82) Lakes and ponds, surface being grown over

27 Building; Buffer 250m and 1000m (732) Mansion (735) House, size class 1 < 150 square metre (736) House, size class 2 > 150 square metre (741) Church (797) Hostel Road, Buffer 250m (5022) Road > 7m, not national road (5024) Road 5-7m, national road (5025) Road 5-7m, not national road Small road, Buffer 250m (5029) Road < 5m, not national road (5061) Public road, good standard (5071) Public road (5082) Public road, poor road Distance small road (5029) Road < 5m, not national road (5061) Public road, good standard (5071) Public road (5082) Public road, poor road

28 TestSignificant VariableHigherLowerMoose kill vs controlHeight of undergrowthXProportion of spruceXProportion of meadowXAverage meters above sea levelXRoe deer vs controlNumber of stemsXMoose kill vs randomProportion clear- cutsXNumber of buildingsXAverage meters above sea levelXRoe deer kill vs randomProportion coniferous forestXAverage meters above sea levelX


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