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Making a difference for a truly clean, green and sustainable New Zealand Modelling weed spread in heterogeneous landscapes NZIMA weeds workshop 17 April.

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Presentation on theme: "Making a difference for a truly clean, green and sustainable New Zealand Modelling weed spread in heterogeneous landscapes NZIMA weeds workshop 17 April."— Presentation transcript:

1 Making a difference for a truly clean, green and sustainable New Zealand Modelling weed spread in heterogeneous landscapes NZIMA weeds workshop 17 April 2007 John Kean (AgResearch, Lincoln) Jake Overton (Landcare Research, Hamilton) Peter Williams (Landcare Research, Nelson) Rowan Buxton (Landcare Research, Lincoln)

2 Overview Why model weeds at the landscape scale? Modelling weed spread in heterogenous landscapes (e.g. PestSpread v.1) Field data for modelling (e.g. hawthorn) A model of a weed model

3 What is a weed? 1.Any plant that is growing where it is unwanted “A weed is a plant that has mastered every survival skill except for learning how to grow in rows.” - Doug Larson “What is a weed? A plant whose virtues have never been discovered.” - Ralph Waldo Emerson

4 What is a weed? 1.Any plant that is growing where it is unwanted “A weed is a plant that has mastered every survival skill except for learning how to grow in rows.” - Doug Larson “What is a weed? A plant whose virtues have never been discovered.” - Ralph Waldo Emerson 2.A town in northern California

5 Why model weeds? (Feedback from DOC, Regional Councils, Biosecurity NZ) Prioritise pests and control efforts Transparency of decision-making Target surveillance Optimising control efficacy Support national and international cooordination Estimate and communicate the difference made Identify research needs

6 Weed prioritisations National Pest Plant Accord (http://www.biosecurity.govt.nz/pests-diseases/plants/accord.htm) Regional Pest Management Strategies (e.g. /pestAndWeeds/RPMS+2005.htm) National Pest Management Strategies (e.g. Prioritisations are largely subjective: expert opinion + qualitative weed risk assessments Can we do better?

7 current distribution potential distribution yr 10 yr 20 yr 30 yr 40 yr 50

8 current distribution potential distribution local population growth (aging + local reproduction) dispersal of propagules

9 stored resources species distributions current, potential, pre-calculated species setup files e.g. gorse, pinus, old man’s beard other spatial information e.g. friction maps for dispersal demography modules e.g. annual herb, tree, vine etc dispersal modules e.g. wind, bird, water etc modelling modules model core model user web server (with GIS) species setup file distribution maps management file predicted distribution maps PestSpread v.1

10 ± age-dependent seed production sigmoid local increase Demography modules 1 ± persistent seed bank

11 SeedlingsJuvenilesAdults Demography modules 2 Seeds

12 classical dispersal kernel nearest neighbour Dispersal modules 1

13 wind ± topography Dispersal modules 2

14 water runoff: direction + flow rate Dispersal modules 3

15 bird dispersal = habitat preference + seed deposition Dispersal modules 4

16 Widespread speciesLimited distribution species TreeCorsican pine Pinus nigra in Twizel Sweet pittosporum Pittosporum undulatum in Kaitaia ShrubScotch broom Cytisus scoparius in Palmerston North Spiny broom Calicotome spinosa in Palmerston North GrassPampas Cortaderia selloana in Palmerston North Pypgrass Ehrharta villosa in Palmerston North VineOld man’s beard Clematis vitalba in Palmerston North White bryony Bryonia cretica in Palmerston North Case study weeds

17 Widespread speciesLimited distribution species TreeCorsican pine stage structured wind Sweet pittosporum stage structured bird dispersal ShrubScotch broom stage structured neighbour + run-off Spiny broom stage structured neighbour + run-off GrassPampas stage structured classical kernel Pypgrass sigmoid neighbour VineOld man’s beard stage structured classical kernel White bryony sigmoid + age bird dispersal Case study weeds

18 NEAREST8 dispersal (10% of cover) SIGMOID local increase Pypgrass assumptions

19 Pypgrass predictions

20 (NB. No seed bank) Seedlings < 2 yr Juveniles yr Adults >14 yr Corsican pine life cycle

21 Wind rose for Twizel in May when wind speed > 5 m/s and temperature > 15 °C Wind dispersal

22 Corsican pine

23 Corsican pine predicted % cover for 2054

24 Seedling < 1 yr Juvenile 1 – 2 yr Mature adult vine > 3 yr Seed dispersal 250 m Old man’s beard life cycle

25 Old man’s beard

26 Old man’s beard predicted % cover

27 Robust pest prioritisation and risk assessment = potential distribution (ultimate risk) + current distribution (scope for additional damage) + change over time (immediacy of risk) + management = cost/benefit of action + value of affected areas ($$ or NHMS) + impact on affected areas What next? PestSpread v.1 PestSpread v.2

28 Points to ponder 1.What is the appropriate spatial scale to be working at? 2.Can we just “scale up” from local models? 3.How much detail about the landscape do we need? 4.Can we really see the landscape from a plant's point of view? 5.How does landscape affect competition/invasibility? 6.Can we legitimately extrapolate model results from one landscape to another, or from one species to another?

29 Aims: 1.To identify the changing drivers determining hawthorn spread 2.To predict hawthorn spread under different landscape and management influences Study site: Porters pass, Canterbury Hawthorn ecology:  Long-lived, slow to mature  Abundant fleshy fruit spread by blackbirds  Seedlings only partially grazing resistant Spread of hawthorn

30 1908 (WA Taylor glass plate, Canterbury Museum)

31 1978 (Ian Whitehouse photo)

32 2005

33 Sampling hawthorn

34 The grand-daddy of them all

35 A successful day in the field

36 Predicting hawthorn age

37 1930

38 1935

39 1940

40 1945

41 1950

42 1955

43 1960

44 1965

45 1970

46 1975

47 1980

48 1985

49 1990

50 1995

51 2000

52 2005

53 Direction from original tree Distance from original tree (m) Hawthorn spread Proportion of 2006 trees

54 Landform Intrinsic rate of increase /yr Hills Gullies Scarps High terraces Low terraces and riverbed Effects of landscape

55 Hawthorn invasion (NB. Log scale)

56 Phase 1 r = /yr Hawthorn invasion (NB. Log scale)

57 Phase 1 r = /yr Phase 2 r = /yr Hawthorn invasion cessation of burning + rabbit control + fertilisers = blackbird nesting sites (NB. Log scale)

58 = ( - ) × [ (+ ) - ] × [ × - ( - )] ×  ( × ) Potential risk of weed potential distribution feasibility and cost of eradication climate change current distribution probability of naturalisation local rate of increase dispersal rate propagule persistence feasibility and cost of control impact on invaded ecosystems value of invaded ecosystems economic social environmental

59 = ( - ) × [ (+ ) - ] × [ × - ( - )] ×  ( × ) Potential risk of weed potential distribution feasibility and cost of eradication climate change current distribution probability of naturalisation local rate of increase dispersal rate propagule persistence feasibility and cost of control impact on invaded ecosystems value of invaded ecosystems economic social environmental needs work well studied potential gains

60 Acknowledgements Department of Conservation Graeme Bourdot (AgResearch, Lincoln) Shona Lamoureaux (AgResearch, Lincoln) James Barringer (Landcare Research, Lincoln) Stephen Ferriss (Landcare Research, Lincoln) Mandy Barron (AgResearch, Lincoln)

61 Rowan invasion at Tekapo


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