Table S3. Growth Rate and Habitat Use Data
Habitat
|
% land-scape
|
% Starling’s Time
|
Normalized Habitat Use Index (% use /
% landscape)
|
Seedling Survival
|
Plant Survival
|
Population Growth Rate (λ)
|
Developed
|
15.3%
|
34.1%
|
0.39
|
49%
|
95-100% (8g)
|
2.1
|
Agricultural
|
16.5%
|
42.0%
|
0.44
|
64%
|
95-98% (6g)
|
1.5
|
Deciduous
|
62.9%
|
20.5%
|
0.06
|
66%
|
90-95% (2.5g)
|
1.4
|
Coniferous
|
5.3%
|
3.5%
|
0.11
|
43%
|
60-80% (1.5g)
|
0.5
|
Summary of data used to parameterize habitat use for European starlings and Oriental bittersweet. The proportion of landscape was evaluated for the region where radio tracking was conducted (LaFleur 2006). Plant survival and mean dry weight biomass was measured across replicate sites from a transplant experiment (seedlings: LaFleur unpublished; adults: Leicht 2005). Bold values are model parameters estimated from data.
Table S4: LULC Reclassifications
Definitions of the reclassification scheme used to translate NOAA data for the model.
Original Class
|
Description
|
Revised Class
|
1
|
Unclassified
|
Unsuitable
|
2
|
Developed, High Intensity
|
Developed
|
3
|
Developed, Medium Intensity
|
Developed
|
4
|
Developed, Low Intensity
|
Developed
|
5
|
Developed, Open Space
|
Developed
|
6
|
Cultivated Crops
|
Agriculture/Scrub/Shrub
|
7
|
Pasture/Hay
|
Agriculture/Scrub/Shrub
|
8
|
Grassland/Herbaceous
|
Agriculture/Scrub/Shrub
|
9
|
Deciduous Forest
|
Deciduous Forest
|
10
|
Evergreen Forest
|
Coniferous Forest
|
11
|
Mixed Forest
|
Coniferous Forest
|
12
|
Scrub/Shrub
|
Agriculture/Scrub/Shrub
|
13
|
Palustrine Forested Wetland
|
Unsuitable
|
14
|
Palustrine Scrub/Shrub Wetland
|
Unsuitable
|
15
|
Palustrine Emergent Wetland (Persistent)
|
Unsuitable
|
16
|
Estuarine Forested Wetland
|
Unsuitable
|
17
|
Estuarine Scrub / Shrub Wetland
|
Unsuitable
|
18
|
Estuarine Emergent Wetland
|
Unsuitable
|
19
|
Unconsolidated Shore
|
Unsuitable
|
20
|
Barren Land
|
Unsuitable
|
21
|
Open Water
|
Unsuitable
|
22
|
Palustrine Aquatic Bed
|
Unsuitable
| Figure S19. Seed dispersal kernel estimates
We used radio tracking data to estimate local bird movements and banding recaptures to estimate larger scale movements in conjunction with gut passage time to produce a seed dispersal kernel. Shown are three characteristic seed retention times (that represent the range) coupled with both local and banding data. We produced a conservative envelop around the kernel chosen for the model (dark line). The inset histogram shows the frequency distribution of the distances traveled by starlings between banding and recapture over an intervals of two days or less. The proportion of seeds deposited in each cell by the kernel chosen for the model (dark line) is shown along the horizontal axis.
Directory: peoplepeople -> Math 4630/5630 Homework 4 Solutions Problem Solving ippeople -> Handling Indivisibilitiespeople -> San José State University Social Science/Psychology Psych 175, Management Psychology, Section 1, Spring 2014people -> YiChang Shihpeople -> Marios S. Pattichis image and video Processing and Communication Lab (ivpcl)people -> Peoples Voice Café Historypeople -> Sa michelson, 2011: Impact of Sea-Spray on the Atmospheric Surface Layer. Bound. Layer Meteor., 140 ( 3 ), 361-381, doi: 10. 1007/s10546-011-9617-1, issn: Jun-14, ids: 807TW, sep 2011 Bao, jw, cw fairall, sa michelsonpeople -> Curriculum vitae sara a. Michelsonpeople -> Curriculum document state board of education howard n. Lee, Cpeople -> A hurricane track density function and empirical orthogonal function approach to predicting seasonal hurricane activity in the Atlantic Basin Elinor Keith April 17, 2007 Abstract
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