Latest Score:

1.8/5

in 2016

score trend is flat over time
Weight: 12%

Forest connectivity is an assessment of how connected large areas of forests are on the landscape. Forest blocks that are separated make it harder for animals and plants to move between patches1. Forests with higher connectivity allow for the exchange of water and nutrients, movement of wildlife, dispersal, genetic interchange between populations, and long distance range shifts of species, such as in response to climate change2,3. Maintaining functional connectivity is critical as forests become more fragmented with urban expansion. Here, forest connectivity is measured using the “Contagion Index” calculated using FragStats software4. A high score means that forest connectivity is not changing from year to year.

1Taylor, P.D., Fahrig, L., Henein, K. and Merriam, G., 1993. Connectivity is a vital element of landscape structure. Oikos, pp.571-573.
2Code of Federal Regulations. 2011. Title 36, Section 219.19.
3Sorenson, E and Osborne, J. 2014. Vermont habitat blocks and habitat connectivity: an analysis using geographic information systems. Available at: http://www.vtfishandwildlife.com/UserFiles/Servers/Server_73079/File/Conserve/Vermont_Habitat_Blocks_and_Habitat_Connectivity.pdf
4McGarigal, K., SA Cushman, and E Ene. 2012. FRAGSTATS v4: Spatial Pattern Analysis Program for Categorical and Continuous Maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. Available at the following web site: http://www.umass.edu/landeco/research/fragstats/fragstats.html

-- Expert interpretation for Forest Connectivity is not available--

The score is calculated using a target value and the historical range of the the entire long-term dataset. The higher the score, the closer this year's value is to the target.

Once the score is computed for each year, the trend in scores over time is calculated. If the trend is significantly positive or negative, the long-term trend is marked as increasing or decreasing respectively.

Component Description
Scored as

Distance between minimum and target (scaled 1-5)

Target value

Long-term mean

Directionality of scores

No change from the long-term mean is better

Minimum value used in scoring

Data minimum - 10% of the range

Maximum value used in scoring

Data maximum + 10% of the range

Using the National Land Cover Database (NLCD)1 we mapped forest cover (41 Deciduous Forest, 42 Evergreen Forest, 43 Mixed Forest, and 90 Woody Wetlands) at 30 meter resolution. The 2019 reprocessed release of the NLCD begins in 2001. We used FragStats2 to compute forest connectivity. We used the 8 cell neighborhood rule with a ‘no sampling’ strategy. We selected ‘Contagion’ as the Landscape Aggregation metric for computation. We set the target for this dataset to be the long-term mean. The current year is scored for where it falls between target and either the lower scoring bounds (dataset minimum minus 10% of the range) or the upper scoring bounds (dataset maximum plus 10% of the range) and the target when values are above the target, scaled to be between 1 and 5.

1US Geological Survey. 2019. National Land Cover Database. Available at: https://www.mrlc.gov/data
2 McGarigal, K., SA Cushman, and E Ene. 2012. FRAGSTATS v4: Spatial Pattern Analysis Program for Categorical and Continuous Maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. Available at the following web site: http://www.umass.edu/landeco/research/fragstats/fragstats.html

STRUCTURE INDICATORS