Prioritizing invasive species monitoring using habitat suitability models

Alycia Crall Catherine S Jarnevich Brendon J Panke Mark J Renz

Habitat Suitability Models

• Inform monitoring and management decisions. • Inform policy.

Two Studies Aggregating Data

• Roadside ground truthing of invasive species models.

• Comparison of Professional and Professional + Volunteer Datasets.

How We Built the Models • Compiled points from a number of survey efforts. • Examples of environmental variables: ▫ Yearly precipitation. ▫ Distance from water. ▫ Clay in soil.

• Maxent 3.3.3a. • 25 iterations.

Black = High Probability White = Low Probability

Wild Parsnip

1 : 4,000,000

Sturgeon Bay

1 : 316,800

Rileys Bay

Little Sturgeon Bay

Sand Bay

1 : 31,680

Study 1

• Test model accuracy. • Compare targeted sampling to “business as

usual” sampling.

Percentage of True and False Negatives by Species

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Spotted knapweed Wild parsnip

False Low

True Low

Percentage of True and False Positives by Species

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Spotted knapweed Wild parsnip

False High

True High

Targeted vs. Non-targeted Targeted Non-

targeted

Wild Parsnip Presences 43 (True positives only) 467

Number of Sites Visited 72 (Sites predicted as present only) 1996

% Wild Parsnip 60% 23%

Chi-square p = 5.733e-12

Study 2 • Comparison of professional datasets and

professional + volunteer datasets.

Wisconsin Counties with Presence Points

Species Counties Represented

by the Professional Data Set

Counties Represented by the Volunteer Data

Set

Counties Unique to the Volunteer Data Set

Counties Represented by the Professional + Volunteer Data Set

Alliaria petiolata 35 31 10 45

Berberis thungbergii 18 5 4 22

Cirsium palustre 9 11 2 11

Polygonum cuspidatum 2 43 41 43

Pastinaca sativa 13 3 2 15

Percent Contribution to the Model

Variables A. petiolata

Professional Data Set

Average annual precipation, 1971-2000 19.3

Maximum NDVI, 2006-2010 15.7

Soil pH 15.2

Soil organic matter 11.4

Percent clay 11.3

Distance to urban areas 8.8

Distance to water 5.8

Average temperature of coldest month, 1971-2000 5.2

Landcover classification 4.7

Tree cover 1.6

Distance to roads 1.2

Variable A. petiolata

Professional Data Set Professional + Volunteer Data Set

Average temperature of coldest month, 1971-2000 5.2 38.6

Maximum NDVI, 2006-2010 15.7 11.3

Distance to urban areas 8.8 9.9

Soil organic matter 11.4 9.5

Percent clay 11.3 6.8

Soil pH 15.2 5.1

Distance to water 5.8 6.1

Average annual precipitation, 1971-2000 19.3 4.9

Landcover classification 4.7 5.2

Tree cover 1.6 1.2

Distance to roads 1.2 1.4

Conclusions • Prioritization ▫ Monitoring. ▫ Control.

• Targeted v. “Business as Usual” ▫ Clear advantages. ▫ Combine best part of both techniques.

• Professional v. Volunteer ▫ Geographical extent.

Thank you • North Central Integrated Pest Management Center. • Beaver Creek Reserve Citizen Science Center. • North Woods CWMA. • Ridges Sanctuary. • Wisconsin Department of Transportation. • GLIFWC. • Wisconsin DNR. • SEWISC. • Chequamegon-Nicolet, Hiawatha, and Ottawa national forests. • Marquette County Conservation Department. • National Park Service. • Mt. Horeb High School. • Milwaukee County Parks.