1. Predicting species distributions for New England invasives

4. Explanatory data layers:
Field collected information: habitat/community type, canopy closure, slope aspect, soil moisture regime
Climate variables: Mean annual precipitation, Mean annual snow fall, Mean annual min & max temperatures, Annual record extreme min & max temperature, Mean annual temperature, Mean length of frost free period, Mean number of growing degree days, Mean annual number of heating degree days: 2 km grid scale.
Topographic variables: DEM - average elevation for 2km grid cell, DEM – range, high and low values for 2km grid cell.
Road influences: Distance to Road (for each IPANE plot point), Length of Roads within each 2km grid cell.
Landuse – landcover: percent land cover of each of 9 classes resampled from 30m resolution to 2 km.

5. IPANE data are used for predictive
modeling. Here is the predicted spread
of Celastrus orbiculatus (from dark areas
to light areas) in New England.
Celastrus orbiculatus
Oriental bittersweet
The uncertainty (variance) is also
measured in the predictive model
(darker areas are most uncertain).
Example of modeled invasive distribution at the regional scale: Oriental bittersweet

6. Local to landscape patterns

7. C. orbiculatus: 251 out of 603 - 41.6 %

8. Is there an effects of land-use or land-use change on the distribution of invasive species in the New England landscape?

9. Land-use change in a local landscape

10. Quantifying land-use change in the landscape over the past 70 years from aerial photography in Connecticut
2000
1970
1951
1934

11. Procedure
Process historical aerial photographs – create geo-corrected mosaic images of 5 different time periods.
Digitize land use features - visual interpretation of aerial mosaics using a suite of LULC categories.
Create a stratified random sampling scheme - Generate 50+ random points for each change category.
Sampling - based upon the IPANE plot protocols

12. Digitizing Example

13. LULC Change Categories
1. Forest - No Change
2. Cultivated Fields - No change
3. Pasture/Meadow - No change
4. Residential/Commercial - No change
5. Abandoned fields to Forest
6. Cultivated fields to Forest
7. Pasture/Meadow to Forest
8. Cultivated Fields to Abandoned to Forest
9. Pasture/Meadow to Abandoned to Forest
10. Cultivated fields to Abandoned fields
11. Pasture/Meadow to Abandoned fields
12. Forest to Residential/Commercial
13. Cultivated fields to Residential/Commercial
14. Pasture to Residential/Commercial
15. Abandoned fields to Residential/Commercial
16. Abandoned fields to Forest to Residential/Commercial
No Change
Agricultural Fields
Reverted to Forest
Abandoned Fields
as of 2003
Conversion to
Residential/
Commercial

14. Final Plot Points
603 in Total: 507 Random, 96 Opportunistic

15. Presence of One or More Invasive Species
All Plots:
363 / 603 or
60.2%
Random Plots:
288 / 507 or
55.4%

16. C. orbiculatus: 251 out of 603 - 41.6 %
Random:
186 / 507
36.7%
1000+ : 3
: 53
: 100

17. B. thunbergii: 199 out of 603 - 33.0 % 27.6% Random: 140 / 507
1000+: 2
: 31
: 47

18. Presence/Absence Individual Species by LULC Groups (From Random Plots: N = 507)

19. ( Abundance of all species combined)
Hierarchy of Invasion
( Abundance of all species combined)
1st: Abandoned Fields as of 2003
(p = .005)
2nd: Agricultural Fields Reverted to Forest
(p < .0001)
3rd: Conversion to Residential / Commercial
4th: Categories with No Change

20. Regression models
Invasive species abundance = f(environmental explanatory variables)
Explanatory variables:
Community type (24 IPANE categories),
Habitat class (4),
Canopy closure,
Slope aspect,
Soil moisture,
LULC (12 or 5),
Distance to Road, Road density,
Distance to nearest building, Building density,
Edge Distance (and type),
Elevation,
Geology,
Soil type and Soil drainage class.

21. Explaining spatial patterns in Oriental bittersweet abundance using regression models
Community type: + Aspen/birch, old fields, forest/field edge, roadsides.
- Oak/pine forests.
LULC type: + conversion to residental/commercial, abandoned fields, fields reverting to forest.
- agricultural fields, no change, especially forest.
Canopy closure: - [moderate to dense canopies]
Edge distance: -
Minor contribution: soils, building distance, prior vegetation cover

22. Explaining spatial patterns in Japanese barberry abundance using regression models
Canopy closure: - [for densest canopy closure]
Community type: + upland red maple, northern hardwoods, birch/aspen, old fields, open fields
- agricultural fields, coniferous forests, oak/pine forests.
LULC: + field reverting to forests
- agricultural fields, forests
Edge distance: -

23. Mid-Spring ADAR:A Possible Remote
Sensing Search Tool for Invasives?