making a difference for a truly clean, green and sustainable new zealand modelling weed spread in...
TRANSCRIPT
Making a difference for a truly clean,green and sustainable New Zealand
Modelling weed spreadin heterogeneous landscapes
NZIMA weeds workshop17 April 2007
John Kean (AgResearch, Lincoln)Jake Overton (Landcare Research, Hamilton)Peter Williams (Landcare Research, Nelson)Rowan Buxton (Landcare Research, Lincoln)
Overview
• Why model weeds at the landscape scale?
• Modelling weed spread in heterogenous landscapes(e.g. PestSpread v.1)
• Field data formodelling(e.g. hawthorn)
• A model of aweed model
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
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 northernCalifornia
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
Weed prioritisations
• National Pest Plant Accord(http://www.biosecurity.govt.nz/pests-diseases/plants/accord.htm)
• Regional Pest Management Strategies(e.g. http://www.ecan.govt.nz/Plans+and+Reports
/pestAndWeeds/RPMS+2005.htm)
• National Pest Management Strategies(e.g. http://www1.maf.govt.nz/pms/cgi/pms.pl)
Prioritisations are largely subjective:expert opinion + qualitative weed risk assessments
Can we do better?
currentdistribution
potentialdistribution
yr 10
yr 20
yr 30
yr 40
yr 50
currentdistribution
potentialdistribution
local population growth(aging + local reproduction)
dispersal of propagules
storedresources
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
modelcore
modeluser
web server(with GIS)
• species setup file• distribution maps• management file
predicteddistribution maps
PestSpread v.1
± age-dependent seed production
sigmoid localincrease
Demography modules 1
± persistent seed bank
Seedlings Juveniles Adults
Demography modules 2
Seeds
classicaldispersal
kernel
nearest neighbour
Dispersal modules 1
wind ± topography
Dispersal modules 2
water runoff: direction + flow rate
Dispersal modules 3
bird dispersal
= habitat preference+ seed deposition
Dispersal modules 4
Widespread species Limited distribution species
Tree Corsican pine
Pinus nigra
in Twizel
Sweet pittosporum
Pittosporum undulatum
in Kaitaia
Shrub Scotch broom
Cytisus scoparius
in Palmerston North
Spiny broom
Calicotome spinosa
in Palmerston North
Grass Pampas
Cortaderia selloana
in Palmerston North
Pypgrass
Ehrharta villosa
in Palmerston North
Vine Old man’s beard
Clematis vitalba
in Palmerston North
White bryony
Bryonia cretica
in Palmerston North
Case study weeds
Widespread species Limited distribution species
Tree Corsican pine
stage structured
wind
Sweet pittosporum
stage structured
bird dispersal
Shrub Scotch broom
stage structured
neighbour + run-off
Spiny broom
stage structured
neighbour + run-off
Grass Pampas
stage structured
classical kernel
Pypgrass
sigmoid
neighbour
Vine Old man’s beard
stage structured
classical kernel
White bryony
sigmoid + age
bird dispersal
Case study weeds
NEAREST8 dispersal(10% of cover)
SIGMOID local increase
Pypgrass assumptions
Pypgrass predictions
(NB. No seed bank)
Seedlings< 2 yr
Juveniles2 - 14 yr
Adults>14 yr
Corsican pine life cycle
Wind rose for Twizel in Maywhen wind speed > 5 m/s and temperature > 15 °C
Wind dispersal
Corsican pine
Corsican pine predicted % coverfor 2054
Seedling< 1 yr
Juvenile1 – 2 yr
Mature adult vine> 3 yr
Seed dispersal
250 m
Old man’s beard life cycle
Old man’s beard
Old man’s beard predicted % cover
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?
PestSpreadv.1
PestSpreadv.2
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?
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
1908 (WA Taylor glass plate, Canterbury Museum)
1978 (Ian Whitehouse photo)
2005
Sampling hawthorn
The grand-daddy of them all
A successful day in the field
y = 1.26x + 7.70
R2 = 0.81
0
30
60
90
0 10 20 30 40 50
Diameter (cm)
Ag
e (
ye
ars
)
Predicting hawthorn age
y = 7.12e0.28x
R2 = 0.70
0
30
60
90
0 3 6 9 12
Height (m)
Ag
e (
ye
ars
)
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
0
0.04
0.08
0.12
0.16
010
020
030
040
050
060
070
080
090
010
0011
0012
0013
0014
0015
0016
0017
0018
00
Pro
p. o
f 2
00
6 t
ree
s
N
NE
E
SE
S
SW
W
NW
Direction from original tree
Distance from original tree (m)
Hawthorn spread
Pro
po
rtio
n o
f 2
006
tree
s
LandformIntrinsic rate
of increase /yr
Hills 0.0833
Gullies 0.0707
Scarps 0.0662
High terraces 0.1341
Low terraces and riverbed 0.1925
Effects of landscape
1
10
100
1000
1925 1935 1945 1955 1965 1975 1985 1995
Year
Re
lati
ve
no
tre
es
pre
se
nt
Hawthorn invasion
(NB. Log scale)
1
10
100
1000
1925 1935 1945 1955 1965 1975 1985 1995
Year
Re
lati
ve
no
tre
es
pre
se
nt
Phase 1r = 0.036 /yr
Hawthorn invasion
(NB. Log scale)
1
10
100
1000
1925 1935 1945 1955 1965 1975 1985 1995
Year
Re
lati
ve
no
tre
es
pre
se
nt
Phase 1r = 0.036 /yr
Phase 2r = 0.126 /yr
Hawthorn invasion
cessation of burning+ rabbit control
+ fertilisers= blackbird nesting sites
(NB. Log scale)
= ( - )
× [ (+ ) - ]
× [ × - ( - )]
× ( × )
Potential risk of weed
potentialdistribution
feasibility and costof eradication
climatechange
currentdistribution
probability ofnaturalisation
local rateof increase
dispersalrate
propagulepersistence
feasibility andcost of control
impact on invadedecosystems
value of invadedecosystems
economicsocial
environmental
= ( - )
× [ (+ ) - ]
× [ × - ( - )]
× ( × )
Potential risk of weed
potentialdistribution
feasibility and costof eradication
climatechange
currentdistribution
probability ofnaturalisation
local rateof increase
dispersalrate
propagulepersistence
feasibility andcost of control
impact on invadedecosystems
value of invadedecosystems
economicsocial
environmental
needs work
well studied
potential gains
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)
Rowan invasion at Tekapo