SITUACIONES ESPECIALES DEL CONSENTIMIENTO:

Explanatory variables: fragmentation, environmental and spatial factors

Environmental data [E]: Physical forest structure of sites was characterized by measuring

understory density and canopy cover within the plots. Understory density (UD) was measured at two heights: 0-1m and 1-3m, to represent different stages of understory growth. As such, this measure may also reflect forest age or level of disturbance. UD was measured with the following steps:

1. A 3 meter long pole with markings every 10cm was positioned vertically at the plot’s center (each plot =10 m x 10 m)

2. The number of marks visible at a height of 0-1m and 1-3m on the pole were recorded for 2m and 3m distance from the pole, in each of 4 cardinal directions, for 8 measures of visibility at each height (0-1m, 1-3m)

3. The 8 measures were used to calculate average understory visibility at each height for each plot (10 plots per site)

4. Understory density was then calculated as the average (from 10 plots) proportion of the pole that was covered (not visible) at each height (UD_1m, UD_3m).

Percent canopy cover was measured with a hand-made densiometer (consisting of a 260 cm2 gridded mirror) held perpendicular to the chest, at breast height. Readings were taken at each corner and in the center of every plot, for a total of 5 measures per plot. Because the densiometer was a flat mirror, the amount of canopy area reflected in each square on the mirror varied

depending on where in the grid that square was. However, that bias was consistent for all plots in all sites, and we were only interested in relative differences in canopy cover among sites, not absolute measures.

Additional Tables

Table B.1. Key to environmental and fragmentation variables. BIO variables were downloaded

from WorldClim (http://www.worldclim.org/bioclim). Further information and formulas used to calculate fragmentation variables can be found with FRAGSTATs documentation

(http://www.umass.edu/landeco/research/fragstats/fragstats.html). Tree diversity statistics were calculated using the R package "BiodiversityR" and tree compositional measures were calculated with R package "vegan" (MDS variables).

Predictor Set Variable ID Description Unit

Fragmentation PD Patch density: Number of patches in the landscape, divided by

total landscape area (m2), multiplied by 10,000 and 100 (to convert to 100 hectares)

Number per 100 hectares

LPI Largest patch index: Quantifies the percentage of total

landscape area comprised by the largest patch: a simple measure of dominance.

Percent

ED Edge density equals the sum of the lengths (m) of all edge

segments in the landscape, divided by the total landscape area (m2), multiplied by10,000 (to convert to hectares).

Meters per hectare

LSI Landscape shape index provides a standardized measure of

total edge or edge density that adjusts for the size of the landscape. LSI increases without limit as landscape shape becomes more irregular and/or as the length of edge within the landscape of the corresponding patch type increases.

NA

AREA_AM AREA equals the area (m2) of the patch, divided by 10,000 (to

convert to hectares).

Hectares FRAC_AM*,

_RA**

Fractal dimension index reflects shape complexity across a range of spatial scales (patch sizes). FRAC equals 2 x

logarithm of patch perimeter divided by the logarithm of patch area; (1<FRAC< 2) FRAC approaches 1 for shapes with very simple perimeters such as squares, and approaches 2 for shapes with highly convoluted, plane-filling perimeters.

NA

PROX_MN, _AM*

Uses a modification of the proximity index developed by Gustafson and Parker (1992) and considers the size and proximity of all patches that are within a specified search radius (64km) of the focal patch. When the search buffer extends beyond the landscape boundary, only patches contained within the landscape are considered in the

computations. PROX increases as the neighborhood (defined by the specified search radius) is increasingly occupied by patches of the same type and as those patches become closer and more contiguous (or less fragmented) in distribution

NA

CONNECT Number of functional joinings between "forest" patches, where each pair of patches is either connected or not based on a user- specified distance criterion (5km). Connectance is reported as a percentage of the maximum possible connectance given the number of patches.

Percent

CA Cumulative area: Sum of patch area (total forest cover) Hectares

Table B.1. cont’d

Environment ALT_EX Elevation above sea level Meters

Tree_SumDbh Total diameter-at-breast-height values per site NA

Avg_CC Average canopy cover Percent

Avg_UD1m Average understory density measured from a height of 0-1m Percent

Avg_UD3m Average understory density measured from a height of 1-3m Percent

BIO1 Annual Mean Temperature Celsius

BIO4 Temperature Seasonality (standard deviation *100) NA

BIO5 Max Temperature of Warmest Month Celsius

BIO6 Min Temperature of Coldest Month Celsius

BIO12 Annual Precipitation Millimeters

BIO13 Precipitation of Wettest Month Millimeters

BIO14 Precipitation of Driest Month Millimeters

BIO15 Precipitation Seasonality (Coefficient of Variation) NA

richness Tree richness, based on tree species data from ten (100m2

each) plots per site

NA

Simpson Simpson diversity index, based on tree species data from each

site

NA

Shannon Shannon diversity index, based on tree species data from each

site

NA

MDS1 Non-metric multidimensional scaling axes calculated in R

package "vegan" based on tree species data each site

NA MDS2

MDS3 MDS4

MDS5

* ―AM‖ (area-weighted mean) equals the sum, across all patches in the landscape, of the corresponding patch metric value multiplied by the proportional abundance of the patch [i.e., patch area (m2) divided by the sum of patch areas].

** ―RA‖ (range) equals the value of the corresponding patch metric for the largest observed value minus the smallest observed value (i.e., the difference between the maximum and minimum observed values) for all patches in the landscape.

Table B.2. Information on Landsat 7 (NASA Landsat Program) Enhanced Thematic Mapper

Plus (ETM+) satellite images (SLC-off, T1 Level Product) published by USGS (glovis.usgs.gov) and used to determine forest cover in the study region. Forest was characterized with Band 7 (wavelength = 2.08-2.35 micrometers, resolution = 30 meters), and analyzed in ArcMap v9.2. Indicated are path, row, image acquisition date, percent cloud cover, and grouping and spectral range, determined from geo-referenced ground data, that was used to distinguish forest from non-forest in ArcMap. All downloaded data were high quality (9).

Band 7