Nonnative Exotic Plant Species Early Detection Progress todate

1
Non-native Exotic Plant Species Early
DetectionProgress to-date
Jason Welborn Sonoran Institute

• Theresa Mau-Crimmins
• National Park Service

2
Three Phases of Invasive Plant Control

• Inventory
• Monitoring
• Management

3
Inventories

• Comprehensive survey
• Sample and predictive model

Small areas (lt5,000 ha?) Large areas
4
Comprehensive Inventories

• Handheld GPS units, computers

5
(No Transcript)
6
(No Transcript)
7
(No Transcript)
8
(No Transcript)
9
Sample-based Inventories

• Lisa Rew et al. Montana State University
• Evaluated 7 survey methods via simulation

• Rew, L.J., B.D. Maxwell, F.L. Dougher and R.
  Aspinall. 2005. Searching for a needle in a
  haystack evaluating survey methods for
  non-indigenous plant species. Biological
  Invasions Special Issue, in press.

10
Proposed Approach Small Parks
Inventory Phase - Establish baseline - Which
species are present
Complete Inventory (iPAQs)
species present
species not yet present
Status Trends Monitoring
Early Detection Monitoring
Monitoring
Objective Bias sampling to maximize efficiency
Predictive Models
Sampling in High SuitabilityAreas
Field Sampling
Beyond NAWMA
Objective check on sampling accuracy
11
Early Detection Monitoring
Predictive Models
Objective Determine whether a species is likely
to occur in a park
Sampling in High SuitabilityAreas
Objective Identify highly suitable
habitat within park units
12
Predictive modeling regional-scale
1C (summer winter) 10 precipitation
(summer winter)
Current distribution
2C (summer winter) 10 precipitation
(summer winter)
3C (summer winter) 30 precipitation
(summer winter)
Best subsets models predicting present
Brassica tournefortii
13
Predictive modeling park-scale
Park-scale predictive modeling can Enable
targeted sampling in areas of suitable habitat
characteristics an ecological niche - where
non-native invasive plants could become
established Facilitate a time-efficient and
cost-effective strategy for managing and
monitoring large land areas Permit park staff to
identify fresh infestations and determine control
measures, thereby preventing further spread into
new areas
14
Environmental variables used to build Park-scale
models

• Edaphic characteristics sand, silt, clay ()
• Elevation
• Slope
• Aspect
• Distance from roads, trails
• Disturbance history

GIS-based calculations
15
Forthcoming report to CESU
16
Early Detection Monitoring
Early Detection sampling point (adaptive?)
Beyond NAWMA sampling point
Predicted suitable habitat for species X in park Y
17
Tribulus terrestris
Polygonum aviculare
Rumex crispus
Sisymbrium irio
Schismus barbatus
Early Detection sampling point (adaptive?)
Composite Map
18
Beyond NAWMA(Stohlgren et al. 2003)

• Purpose QA/QC estimates of field efforts
• 10 of field effort
• Randomly located

• Stohlgren, T.J., T.D. Barnett and S.S. Simonson.
  2003. Beyond North American weed management
  standards. Retrieved from http//science.nature.go
  v/im/monitor/meetings/FtCollins_02/StohlgrenBeyond
  NAWMA.pdf

19
Proposed Approach Large Parks
Inventory Phase - Establish baseline - Which
species are present
Sample Inventory
species present
species not yet present
Status Trends Monitoring
Early Detection Monitoring
Monitoring
Objective Bias sampling to maximize efficiency
Predictive Models
Sampling in High SuitabilityAreas
Field Sampling
Beyond NAWMA
Objective check on sampling accuracy