invasion ecology, climate change, and prediction · invasion ecology, climate change, and...
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Invasion Ecology, Climate Change, and Prediction
[email protected] Web Page http://www.NIISS.org
Tom Stohlgren, Catherine Jarnevich, Tracy Holcombe, Jeff MorisetteGordon Rodda, Bob Reed, Lea Bonewell (USGS)
Becky Kao, Steve Aulenbach, Michael Keller, David Schimal (NEON)Sunil Kumar, Paul Evangelista, Dave Barnett, Greg Newman, Ben White, and John Norman (CSU),
Mingyang Li (China), with help from . . .Rick Shory, Mohammed Kalkhan, Jim Graham, Sara Simonson (NREL),
John Kartesz (BONAP), Tom Armstrong, Sharon Gross, June Thormodsgard, David Greenlee, Chandra Giri, Pam Fuller (USGS), Curt Flather (USFS), John Schnase,
Jeff Pedelty, Woody Turner (NASA) and many others!
Created Sept. 4, 2008
What is an invasive species?
Official U.S. definition of invasive species provided in Executive Order 13112 signed by President William Clinton on February 3, 1999.
"Invasive species" means an alien species whose introduction does or is likely to cause economic or environmental harm or harm to human health.
U.S. Department of the InteriorU.S. Geological Survey
Major Points:
• Harmful non-native plants, animals, and pathogens continue to spread globally.• Hot spots of native diversity are often hot spots of invasion.• Invasions can significantly harm the environment, economy, and human health. • It is important to document, map, and predict harmful invading species to protect the environment, economy, and human health.
Invasive Species: the #1 environmental threat of the 21st
Century
Economic costs ($120B/yr), environmental costs, and costs to human health.
U.S. Department of the InteriorU.S. Geological Survey
"Associated damages and costs of controlling aquatic invaders in the United States are estimated to be $9 billion annually." (Pimentel, 2003)
"The most serious aquatic invading species based on damages and control in terms of millions of dollars per year are fishes ($5400); zebra and quagga mussels ($500); others ($3000)." (Pimentel, 2003)
March 15, 2008 (California] - "...In California, $87 million in taxpayer funds goes to fighting invasive plants and animals every year," Cal-HIP says." (Home invaders: Pretty plants turn ugly fast) (San Francisco Chronicle)
Annual Aquatic Invasive Species cost estimates from Pimentel, 2003 and Simberloff 1996
Fish $5.4 bil.*Zebra and quagga mussels $1 bil.Asiatic clam $1 bil.West Nile Virus (WNV) $1 bil.Aquatic plants $500 mil.*Shipworm $205 mil.Green Crab $100 mil.Boll weevil - > $50 bil.Leafy spurge - $110 mil. (1990)European gypsy moth - $764 mil. (1981)Asian gypsy moth - $20 mil.Sri Lankan Hydrilla /water hyacinth - $100 mil.
* mil. = million | bil. = billion
Pay me now, AND Pay me later!
How did this happen!
A Brief History Of the World
170 million years ago The past million years
The past 12,000 years
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1920 1940 1960 1980 2000 2020
Year
Impo
rts
(x $
1 M
)
1010.51111.51212.51313.51414.515
Mea
n Te
mp
(C)
Temp.
Imports
The past 80 years
Musk thistle, yellow sweetclover, and brome grassesCarduus
nutans
L., Melilotus
officinalis
L., Bromus
spp.
Grime, J.P. (1973) Competitive exclusion in herbaceous vegetation. ...
Charles EltonCharles Darwin
Robert MacArthur& E.O. Wilson
THEORY
Early Paradigm
Islands (species-poor areas) are easily invaded (open niches, unused resources).
Competition is a major force structuring plant communities.
Ecosystems are in equilibrium (and immigration is offset by extinction).
Species-rich areas are less prone to invasion (few open niches, few available resources, competitive exclusion).
“…diverse communities will probably require minimal maintenance and monitoring because they are generally effective at excluding undesirable invaders.”
Kennedy TA, S. Naeem, KM Howe, JMH Knops, D. Tilman, and P. Reich. Biodiversity as a barrier to ecological invasion. Nature 2002; 417:636-638.
PhotoCourtesyOf CiniBrown.
Saturation?
EXPERIMENTALEVIDENCE
1999
2002
SCALE MATTERS! 1-m2
subplots four 1000-m2
plots
Two Rocky Mt. veg. types positive positive
Two Grassland veg. types negative positive
1999 Hot Spots Paper
Fridley, J.D., Stachowicz, J.J., Naeem, S., Sax, D.F., Seabloom, E.W., Smith, M.D., Stohlgren, T.J., Tilman, D., and Von Holle, B. 2007. The invasion paradox: reconciling pattern and process in species invasions.Ecology 88:3-17.
PhotoCourtesyOf CiniBrown.Saturation?
Buyer beware of small plots!
Small-scale measurements?
Do they Scale-Up?
U.S. Department of the InteriorU.S. Geological Survey
15 % Sample
U.S. Department of the InteriorU.S. Geological Survey
15 % Sample
Madame Monet and Her Son by Claude Monet
The Theory of Island Bias-Geography?
ContinentArea
(km²)
Africa-Eurasia 84,000,000The Americas 41,000,000Antarctica 13,000,000Australia 7,600,000Continent Total 145,600,000
Islands >2500km2 9,415,680Islands >1000km2 119,362Other Notable 74,050Island Total 9,609,092
% island Land area 6.2
What’s happening on the other 93.8 % of the Globe???
Leafy spurge (Euphorbia esula L.) in Beaver Meadows,Rocky Mountain National Park, Colorado
Gamma diversity may greatly affects alpha diversity, but this is very difficult to measure!
d
m
y = 0.1112x - 15.812R2 = 0.74P < 0.001
-10
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Landscape Native Species Pool (est. in 100 plots)
Land
scap
e E
xotic
Spe
cies
Poo
(est
. in
100
Plo
ts)
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0 5 10 15 20 25 30 35 40Number of Plots (0.1ha)
a
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o
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a
Aspen
Wet Mdw
Aspen
Wet Mdw
Dry MdwDry Mdw
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Number of Plots (0.1ha)
Exot
ic S
peci
es R
ichn
ess
Nat
ive
Spec
ies
Ric
hnes
s
Aspen
Wet Mdw
Dry Mdw
Aspen
Wet Mdw
Dry Mdw
Estimate-S curves free software
From Currie 1991, cited in Huston 1994
Species Richness and Latitude
1. Plants. Birds,Mammals,Amphibians,Reptiles . . .all show the samegeneral pattern.
2. Total species richness or richnessof any one groupmay be predictablefrom a few biological orenvironmental factors.
> 1080
> 170
Native plant species/county
Non-native plant species/county
Stohlgren TJ, D. Barnett, and J. Kartesz. 2003. The rich get richer: patterns of plant invasions in the United States. Frontiers in Ecology and the Environment. 1:11-14
2003
Chytrỳ
et al. 2005, Invasion by alien plants in the Czech Republic: a quantitative assessmentacross habitats. Preslia, Praha, 77:339-354.
Czech Republic
Richardson et al. 2005. Ecoscience12(3) 391-402.
South Africa
Native bird species/county
Non-indigenous bird species/county
Stohlgren, T.J., D. Barnett, C. Flather, P. Fuller, B. Peterjohn, J. Kartesz, and L.L. Master. 2005. Species richness and patterns of invasion in plants, birds, and fishes in the United States. Biological Invasions 8: 427-457.
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0 0.2 0.4 0.6 0.8 1 1.2 1.4
All Counties
R2
= 0.90y = 0.52x2 +0.07x + 0.001
Stohlgren, T.J., D. Barnett, C. Flather, J. Kartesz, and B. Peterjohn. 2005. Plant species invasions along the latitudinal gradient in the United States. Ecology 86: 2298-2309.
Stohlgren, T.J., D. Barnett, C. Flather, P. Fuller, B. Peterjohn, J. Kartesz, and L.L. Master. 2005. Species richness and patterns of invasion in plants, birds, and fishes in the United States. Biological Invasions 8: 427-457.
Native plant species/county
Non-native plant species/county
Native bird species/county
Non-indigenous bird species/county
Plants Birds
Native Plant Species Density (#/km2)
Non
-nat
ive
Plan
t Spe
cies
D
ensi
ty (#
/km
2 )
Non-native Species Established in Species-Rich Counties
U.S. Department of the InteriorU.S. Geological SurveyAllen JA, CS Brown, and TJ Stohlgren. 2008, Non-native plant invasions in United
States National Parks. Biological Invasions (In Press)
U.S. Department of the InteriorU.S. Geological Survey
0 500 1000 1500 2000NATSP
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OS
P
-2 -1 0 1 2 3 4LNATSPDEN
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PD
EN
Relationship of Native and Non-Native Plant SpeciesIn 214 National Park Units in the United States
y = 0.09 x + 43.78R2 = 0.15 P < 0.0001
y = 1.11 x – 0.96R2 = 0.86 P < 0.0001
Native Species Native Species Density
Exo
tic S
peci
es D
ensi
ty
Exo
tic S
peci
es
1.
The 10 to 20% rule2.
High PredictabilityAllen JA, CS Brown, and TJ Stohlgren. 2008, Non-native plant invasions in United States National Parks. Biological Invasions (In Press)
1.
Immigration (invasion) >> Extinction (higher for plants; higher on mainland)
2. In which communities are they settling??????
Species Native Naturalized Introductions
Presumed/Possibly Extinct
Ratio ofImmigration to Extinction
PlantsCont. U.S
16630 2892 89 32.5 to 1
PlantsHawaii
1197 1051 89 11.8 to 1
BirdsCont. U.S.
721 30 6 5 to 1
Birds Hawaii
98 46 24 1.9 to 1
The 400-year ExperimentCoexistence of Native and Exotic Species in the United States
Source: Curt Flather -- Counts of species based on G-Ranks Modified such that exotics mean not native to the lower 48 the modification subtracts the N-rank exotic count from the G-rank exotic count for the Continental numbers. John Kartesz estimate of plant extinctions.
Stohlgren TJ, Barnett B, Jarnevich C, Flather C, and Kartesz
J. 2008.The myth of plant species saturation. Ecology Letters 11: 313-326.
Saturation?
y = 5E-177x54.009
R2 = 0.445
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1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Year
Non
-nat
ive
Plan
t Spe
cies
R
ichn
ess
…counties across all states,
y = 3.5541x - 6607.1R2 = 0.474
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1920 1940 1960 1980 2000 2020
Year
Num
ber o
f Non
-nat
ive
Plan
t Sp
ecie
s/St
ate ID
MTORWAWY
and at the state and
and regional scale.
y = 5.1729x - 9520.5R2 = 0.9921
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1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
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-nat
ive
Spec
ies
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hnes
s -
Five
Sta
te R
egio
n1. Exotics Gamma diversity increasing at all scales2. Counties registering the greatest increases
-- caveat on reporting effort.
Subregions (counties)Small regions (individual states)Large Region (5-state area)
Plants
Stohlgren TJ, Barnett B, Jarnevich C, Flather C, and Kartesz
J. 2008.The myth of plant species saturation. Ecology Letters 11: 313-326.
The Invasion is just beginning(no sign of saturation)
The Rich Get Richer(The Good Life)
Smaller is better
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All Counties
R2
= 0.90y = 0.52x2 +0.07x + 0.001
Native Plant Species Density (#/km2)
Non
-nat
ive
Plan
t Spe
cies
D
ensi
ty (#
/km
2 )
The Problem:•Reactive not proactive•Surveys are ineffective•Which species?•Which areas?• Triage
Let’s Recap:
The Invasion is just beginning(no sign of saturation)
The Rich Get Richer(The Good Life)
Smaller is better
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All Counties
R2
= 0.90y = 0.52x2 +0.07x + 0.001
Native Plant Species Density (#/km2)
Non
-nat
ive
Plan
t Spe
cies
D
ensi
ty (#
/km
2 )
Incidence per million
.01-9.99 10-99.99 >=100 Any WNV Activity
WNV Neuroinvasive Disease Incidence, by County, US, 1999WNV Neuroinvasive Disease Incidence, by County, US, 1999
N=59
http://www.fundcdc.org/documents/CPH06-22-07Vector-BorneFINAL.ppt#873,17,Slide 17
CDC
Can we predict invasions?Can we monitor the leading edge?
WNV Neuroinvasive Disease Incidence, by County, US, 2000WNV Neuroinvasive Disease Incidence, by County, US, 2000
Incidence per million
.01-9.99 10-99.99 >=100 Any WNV Activity
N=19
http://www.fundcdc.org/documents/CPH06-22-07Vector-BorneFINAL.ppt#873,17,Slide 17
CDC
WNV Neuroinvasive Disease Incidence, by County, US, 2001WNV Neuroinvasive Disease Incidence, by County, US, 2001
Incidence per million
.01-9.99 10-99.99 >=100 Any WNV Activity
N=64
http://www.fundcdc.org/documents/CPH06-22-07Vector-BorneFINAL.ppt#873,17,Slide 17
CDC
WNV Neuroinvasive Disease Incidence, by County, US, 2002WNV Neuroinvasive Disease Incidence, by County, US, 2002
Incidence per million
.01-9.99 10-99.99 >=100 Any WNV Activity
N=2,946
http://www.fundcdc.org/documents/CPH06-22-07Vector-BorneFINAL.ppt#873,17,Slide 17
CDC
WNV Neuroinvasive Disease Incidence, by County, US, 2003WNV Neuroinvasive Disease Incidence, by County, US, 2003
Incidence per million
.01-9.99 10-99.99 >=100 Any WNV Activity
N=2,866
http://www.fundcdc.org/documents/CPH06-22-07Vector-BorneFINAL.ppt#873,17,Slide 17
CDC
WNV Neuroinvasive Disease Incidence, by County, US, 2004WNV Neuroinvasive Disease Incidence, by County, US, 2004
Incidence per million
.01-9.99 10-99.99 >=100 Any WNV Activity
N=1,148
http://www.fundcdc.org/documents/CPH06-22-07Vector-BorneFINAL.ppt#873,17,Slide 17
CDC
(A)
0 10050 Miles
Refuge or National Park
Hart Mt. NWROregon
Akebia quinata (chocolate vine)
Phytophthora ramorum(sudden oak death)
From Patternsto Forecasting
U.S. Department of the InteriorU.S. Geological Survey
Responsevariable
Predictorvariables
Modelpredictions
Modelalgorithm
Example: Potential habitat distribution of invasive plant dalmation toadflax (Linaria dalmatica) in Colorado, USA
-Presence only-Presence with
pseudo-absence-Presence-absence-Count/abundance
Different environmental variables such as:-Topographic-Climatic-Soil-Geology-Disturbance
Different modelingmethods such as:-Maxent-GARP-Multiple regression-Logistic regression-CART
-Map of probability of occurrence
-Map of predicted count/abundance
+Model
evaluation
Modelvalidation
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Presence dataEnvironmental
layers
Maxent
Predicted probability
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0
100
PrecipitationSlope
Elevation
Temperature
Understanding the drivers and predictors of change
U.S. Department of the InteriorU.S. Geological Survey
±
0 5 102.5 km
±
0 5 102.5 km
±
0 5 102.5 km
±
0 5 102.5 km
±
0 5 102.5 km
±
0 5 102.5 km
Predicted potential distribution of cheat grass in Rocky Mountain National Park, Colorado
Presence in 1996 (14) Presence in 1999 (21) Presence in 2007 (38)
Predictions based on 1996 data Predictions based on 1999 data Predictions based on 2007 data
Potentialprobability
0.0
0.10.2
0.99
AUC=0.99 AUC=0.99 AUC=0.99
Jim Bromberg, Cini Brown, Sunil Kumar
U.S. Department of the InteriorU.S. Geological Survey
0 1,000500 km
-
Potential habitat distribution for White Pine Blister Rust (Cronartium ribicola) in the Western United States
High
Relative habitat suitability
Low
Medium
Percent contribution ofpredictors-Growing degree days (47.7%)-No. frost days (25.3%)-Elevation (5.3%)-Max. temperature (4.4%)-Radiation (3.8%)
(Maxent model; based on 918 presence records from multiple sources)
AUC = 0.9975% data Training25% data Testing
Tracy Holcombe PhD dissertation (In Prep)
U.S. Department of the InteriorU.S. Geological Survey
1. Growing degree days
2. Elevation
3. Seasonality
4. Geology
5. Humidity
U.S. Department of the InteriorU.S. Geological Survey
Growing degree days Elevation
Temperatureseasonality Humidity
National Ecological Observatory Network (NEON)
Continental-scale climate change
Effects of urban and exurban development
Forest management
Agriculture and biofuels
Invasive species and infectious diseases
Climate change effects through the water cycle (rain/snow, permafrost, runoff)
Nitrogen deposition
Ecohydrology www.NEONINC.org
Combined Model Current Climate
Potential 2035 Climate
California Model Carolinas ModelLonicera japonica (Japanese honeysuckle)
California CarolinasFrost Days 48.2% Dist_Water
22.9%
Geology 12.8% Geology 18.3%
Precip. Dry Month 10.4% EVI Mean 13.8%
North Aspect 7.3% Radiation 12.6%
Model Drivers
Mean Temp Dry Qtr
31.2%
Precip. Cold Qtr
22.4%
Mean Temp Wet Qtr 10.5%
Elevation 9.5%
Mean Temp. Dry Qtr 32.7%
Precip. Cold Qrt
20.9%
Mean Temp Wet Qrt. 13.5%
Precip
Seasonality 8.5%
ExtrapolationsIn Space
EcologicalForecasting
Site-SpecificModels
NEON Catherine
Africanized Honey Bees
1. Quantifying past climate trends
2. Bracketing future climate change scenarios from existing or new models
3. Forecasting species range shifts based on current distributions and interdisciplinary datasets from Biology, Water, Mapping, and Geology.
5. Isolating background rates of spread from those caused by climate change, land use change, or other causes.
4. Testing various models on many speciesat multiple spatial scales
6. Getting the information to on-the-
ground managers for prevention, “watch lists,”
risk assessments, early detection, rapid response, control, and restoration.
Invasive Species and Climate Change
Lonicera japonica
Conversion to Urban (1992-2001)Stohlgren, TJ, CS Jarnevich, C Giri. Modeling the Human Invader (In Review)
(from 30 m cells to the nation)
Class(NLCD1992-30m) Area (ha)
Converted to urban class in NLCD2001 (ha) Percentage(%)
Barren 9257699 10716 0.115
Forest 213527204 905543 0.424
Grass/shrub 284195691 416603 0.147
Agriculture 182456109 803736 0.441
Wetlands 37392477 89750 0.240
Are we trading forest carbon and food production for suburbs?
What are we landscaping with?
Potential urban areas
Based on NLCD1992
Tested with NLCD2001
Important predictors:Frost days (35.8%)Elevation (19%)Growing degree days (7.3%)Slope (6.8%)93% AUC
0 10 20 30
0.60
0.50
0.40
0.30
0.20
0.10
Pro
babi
lity
0 2000 4000 6000 8000
Growing Degree Days
0.60
0.50
0.40
0.30
0.20
0.10
Elevation (m)
0.64
0.60
0.54
0.52
0.62
0.58
0.56Pro
babi
lity
Frost Days
0.64
0.60
0.52
0.48
0.56
0.68
Pro
babi
lity
0 1000 2000 3000 40000 100 200 300
Slope (%)
0.44
Pro
babi
lity
Important Predictors for the Human Invader
What to do about it: Management and Modeling Issues
Not enough funding to battle all species in all areas.
Pick your battles wisely (Triage).
Smart Surveys and Modeling Can Help!
Which species?Which areas?
Predicting Invasive Species Into New Territory:Colorado as a case study
Drucker, H., CS Brown, and TJ Stohlgren. 2008. DEVELOPING REGIONAL INVASIVE SPECIES WATCH LISTS: COLORADO AS A CASE STUDY. Plant Science and Management (In Press).
Prioritizing Criteria:•Proximity•Habitat Similarities•Life History Traits •Threats•Control Methods
Which species?Create “watch lists”
*data are being gathered for the mid-south that will improve the models
U.S. Department of the InteriorU.S. Geological Survey
Which areas?Create “forecasts”
Jarnevich CS and TJ Stohlgren. 2008. Near term climate projections for invasive species distributions. Biological Invasions (on line) http://www.springerlink.com/content/n5707lx685430766/fulltext.html
Take Home Messages
The world is one continent again (global trade)
We’re not stopping many invaders (32 to 1)
The rich get richer! (The good life!)
Humans contribute to the invasion story.
Invaders cost us a lot of money as taxpayers, and they do harm.
Caveats –
Forecasting???
The Human Factor
For more information see [email protected]
Thank You for inviting me
But it sure is fun!
Thank you USGS, NASA, NEON, USFWS, USDA Forest Service for funding.(It’s a team effort)
Any?s