Absecon Forcarb Final

7/28/2019 Absecon Forcarb Final

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Forest Carbon Sequestration in Absecon, NJ


Samantha AndersonCasey Ghilardi

Vinh Lang

Environmental Issues 4300Spring 2013


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Table of ContentsAbstract2

Introduction..2 -3Methods....3 -4

Forest Area Sampling...3-4

Residential Area Sampling..4Analysis4-5Models..4-5

Results..6

Discussion.6-8Sources of Error7-8

Conclusion...8

Sources.9

Appendix..10-17Tables10-11

Figues12-17


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Abstract

The city of Absecon, NJ is seeking certification for the Sustainable Jersey program and

the Richard Stockton College Environmental Issues senior level class assessed the amount of

CO2 being emitted by the town in the form of waste, electricity, and transportation. By also

calculating forest carbon sequestration, Absecon can see the differences in emissions and storage

capabilities of the town, and try to remedy the large discrepancy. The forests of Absecon are

currently holding almost 38,000 tons of carbon, but the towns emissions are much greater. This

information may provide Absecon with a new view regarding the management of its natural

resources.

Introduction

Carbon sequestration is a vector in the carbon cycle by which atmospheric carbon (CO2)

is stored in vegetation and soils. Sequestration is variable across the landscape due to vegetative

patterns resulting from land use as well as climate change (often a result of physical and

chemical process variation). Because of the unique ability of terrestrial carbon sequestration to

mitigate carbon emissions into the atmosphere, it is believed that vegetation is an important

resource to evaluate for Absecon.

By taking an inventory of the carbon found within Absecons forests, we will attempt to

create a baseline to evaluate present carbon storage. In establishing this frame of reference, it

will be possible for future studies to quantify the changes in carbon storage as well as rate of

sequestration, which are directly correlated to changes in climate. Also, by investigating

sequestration in an area of various land use, the results could lead to potential amendments of

natural resource use.


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Ultimately, the results of our inventory will be compared with other data to verify

whether Absecon is using the resource in an advantageous sustainable manner as compared to

other municipalities, or whether there are ways in which Absecon can implement practices to

increase sustainability and carbon sequestration productivity to achieve a successful threshold.

Methods

Due to the complex nature of forest inventorying within urbanized areas, for purposes of

simplicity and accuracy, forest inventory of the city was stratified into 2 segments, forested land

and residential areas. Forested land was comprised of the larger areas of contiguous forest, and

residential areas consisted of urban and suburban areas where trees are mainly found on

individual lots.

ArcGIS and Google Maps were used to preliminarily identify public parks and other

large forested areas for sampling. Forest acreage was found using the 4100-4300 categories

classified under the Anderson Land Use Classification system of 2007 which included

coniferous, deciduous, and mixed forest types. Similarly, residential areas were classified in the

1100 category of the Classification System, which included high, medium, low, and rural density

units. The city was further subdivided into 6 sampling areas based on the six census block groups

in the town so that each area was equally represented within the samples.

Forest Area Sampling

For forested land, plots were evenly distributed at an interval of five chains (330 feet)

within the previously selected forested areas. Each plot was taken using a basal area factor

(BAF) of 10, and the plot center was assessed to maintain a minimum distance of 1 chain (66

feet) away from any forest edge. For each in tree: species, height, diameter at breast height

(DBH), and condition were recorded. Heights of trees were measured using a Haglof laser


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hypsometer, or a clinometer, and DBH was measured with a diameter tape to the nearest tenth of

an inch.

Residential Area Sampling

Since much of Absecon is developed, a large percentage of trees occur on private

commercial or residential land. To compensate for this, urban and suburban areas were

inventoried using windshield surveys. To begin, random points were distributed within city

limits using an online random point generator. Any block that contained a point was surveyed.

Surveying involved a complete lap around the block and tallying front yard trees by species.

Only native species were included, ornamentals and non-natives were excluded. Average DBH

and height were ocularly estimated for each block. To compensate for not having access to

backyards, all values were doubled under the assumption that the front yards are representative

of the backyards.

Analysis

NED-2 software produced by the US Forest Service was used in analysis which will be

discussed further in the models section of this paper. Inventory data for forest and residential

areas were compiled separately and then expanded out to their respective acreages found in the

2007 Atlantic County Land use/Land cover maps downloaded from the NJ DEP website.

Models

A variety of modeling software packages were implemented and tested. While each had

their own strengths and weaknesses, NED was ultimately chosen for the analysis.

The initial software package utilized was I-Tree from the US Forest Service. This

software package was designed for urban tree inventory and analysis, and can quantify

ecosystem values (US dollars) and amounts. Some problems encountered were overly complex


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interface made data entry difficult, and an extensive list of variables needed for even the most

basic processing made plots too inefficient. Further problems included non-local data processing

which created a time barrier, and analysis of carbon was based around land use allocations.

Explanations of the models used to create carbon estimations were not available.

The next software package tested was NED-2, also from the US Forest Service. NED had

the advantage of being very user friendly in terms of data collection and entry. All variables were

user selected and could be modified to meet any user needs. Carbon estimations are created using

biomass regressions based on the works of Jenkins et al. 2003. For more information, please

refer to the NED manual, which goes into more detail. Another benefit NED had was it allocated

carbon as a function of tree segments (stem, branch, foliage etc.), rather than land use.

After NED, FVS (Forest Vegetation Simulator) was tested. Ease of use and interface was

easier than I-Tree, but more complicated then NED as it requires three separate file types to

access one plot. FVS can model carbon, but further research found that it runs the same model

(biomass regressions based on Jenkins et al 2003) as NED. One distinct benefit of FVS is that it

is comprised of a series of growth models, so it can model a stand as it changes over time. This

stand development can change carbon stocks, which is difficult to account for.

An additional stand-alone model was found called FORCARB. This model was much

more sophisticated and took into account factors such as growth, decay, soil carbon, and much

more. This model was not able to be tested, as the model is very difficult to decipher for

untrained personnel.

NED was chosen as the software to use due to its ease of use, and ability to differentiate

carbon stocks per tree segment rather than land use.


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Results

For forested land, carbon storage was found to be 35.88 tons per acre (Table 1), with the

bulk being held in stem wood biomass. Forested land was found to make up 606.71 acres of

Absecon based on the 2007 Atlantic County land use map, which equates to a total of 21,768

tons of carbon held in the towns forestland.

Residential areas were found to have a more modest amount of carbon storage with 11.96

tons per acre, but in terms of area, residential land made up roughly double the area of forest land

for a total of 1296.28 acres. When calculated out, this is equal to a total of 15,506 tons of carbon

stored in trees. Total current carbon storage for residential and forested lands in Absecon is equal

to about 37,274 tons.

Discussion

Some interesting trends emerged from the survey data. As noted in Tables 3 and 4, the

size distribution of trees varied much more in forested land than residential. For residential land,

the trees were mostly larger older oaks, while in the forested areas the size distribution was more

variable. Another unique observation concerning residential carbon is the lack of carbon held in

dead standing/down woody debris. Many people will remove dead property trees, as standing

dead trees can pose health and safety hazards to people and property.

Based on discussions with other groups working on the different aspects of this project, it

was noted that the total amount of carbon that Absecons forests and residential areas are

currently storing is roughly equivalent to the amount of CO2 emissions being released only by

residential electricity use. This means that the amount of CO2 being released by all other aspects

of the town i.e. commercial and residential waste, commercial energy, and transportation cannot

be compensated for by the towns forests.


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Sources of Error

While possible biases and sources of error were taken into consideration, there is a

certain amount of error that is unavoidable due to the complexity of the project. All possible

measures were taken to try to minimize controllable error due to sampling design. Determination

of amount currently stored was the objective, as rate of sequestration is difficult to determine.

Growth data is required to infer the rate of sequestration, which requires coring of trees. Since

this project is focused on public and residential lands, coring trees was not possible.

The largest source of error can be attributed to the fact that sampling could not be

performed for a large area of forested land due to property boundaries. Large areas of forested

land to the southwest, while qualifying for sampling, could not be accessed as the land belongs to

Atlantic City Water Supply and is surrounded by a fence. Likewise, residential sampling was

subject to the same difficulties. Private property boundaries must be respected, so trees within

residential plots could not be precisely measured.

Next, forest sampling is not entirely representative for every forest patch in Absecon, as

the forests in the town are heavily fragmented by housing developments, roads, and businesses.

The presence of places such as abandoned farm fields that are extremely overgrown with

secondary successional species such as red cedar, dense mountain laurel, and many non-native

species add error. These areas were vastly different from the usual oak-pine that made up the

majority of the forested areas in the town.

A problem unique to the residential inventory was the construction of new apartment

complexes within the city. While these are still classified under residential land use, the

measurements taken from surveys are not representative of the tree composition of these

developments


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Additionally, no commercial areas were surveyed at all. While the presence of trees in

these areas is minimal, it may be beneficial to incorporate these areas in future surveys.

Conclusion

In the event that the town would like to investigate this subject further, it is recommended

that a proper forest and urban tree carbon inventory be carried out by professionals. Additionally,

this report does not incorporate the effects of management decisions on rate or amount of

sequestration. Young seedlings will sequester carbon at a much higher rate due to rapid growth,

and lower density stands will have higher rates of sequestration than dense stands. Therefore it is

suggested that a professional forester be consulted to develop a forest/ urban tree management

plan if maximizing carbon sequestration is a priority for the town.


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Sources

GeoMidpoint. (2013).Random point generator. Retrieved from

http://www.geomidpoint.com/random/

NJDEP. (2007, January 1).Anderson land use land cover classification system. Retrieved from

http://www.state.nj.us/dep/gis/digidownload/metadata/lulc02/anderson2002.html

NJDEP. (2013, March 1).Njdep gis data. Retrieved from http://www.nj.gov/dep/gis/lists.html

Twery, M., Knopp, P., Thomasma, S., & Nute, D. (2011, October).Ned-2 user's guide. Retrieved

from http://www.nrs.fs.fed.us/pubs/gtr/gtr_nrs85.pdf

Zimmermann, George. (2013). Personal communication.

Zipse, William. (2013). Personal communication.


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Appendix

Table 2. Distribution of Carbon within Residential Land

Carbon in tons Live trees Dead trees TOTAL

Foliage Biomass 261 0 261

Stem Wood

Biomass 8,417 0 8,417

Stem Bark

Biomass 1,672 0 1,672

Branch Biomass 2,699 0 2,699

Aboveground

Biomass 13,048 0 13,048

Coarse Root

Biomass 2,458 0 2,458

Total Biomass 15,506 0 15,506

Table 1. Distribution of Carbon within Forested Land

Carbon in tons Live trees Dead trees TOTAL

Foliage Biomass 508 86 594

Stem Wood

Biomass 9,064 1,703 10,767

Stem Bark

Biomass 1,838 378 2,217

Branch Biomass 3,620 975 4,595

Aboveground

Biomass 15,030 3,143 18,174

Coarse Root

Biomass 2,980 614 3,594

Total Biomass 18,011 3,758 21,768


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Table 4. Trees/acre based on DBH and species for forested land

species < 7.00 8 10 12 14 16 18 20 22 > 23.00

white oak 118.8 16.3 9.3 2.7 0 1.3 0 0 0 0scarlet oak 31 32.3 26.1 3.8 4 0.8 0 0 0 0

pitch pine 9 5.4 5.2 6.4 3.6 3 0.5 0 0 0.3

shortleaf pine 0 7.4 4.1 2.9 3.5 1.3 0 0 0 0

American holly 0 0 1.7 0 0 0 0 0 0 0

Table 3. Trees/Acre based on DBH and species for residential

Species < 7.00 8 10 12 14 16 18 20 22 > 23.00

scarlet oak 0 0 0.4 0.3 2.5 2 5.1 0 0 0.2white oak 0 0 0.2 0.6 2.2 2.6 0 0.1 0 0

American holly 0 0 0.6 0 0 0 0 0 0 0

shortleaf pine 0 0 0 0.2 0 0.1 0 0 0 0

pitch pine 0 0 0 0.3 0 0 0 0 0 0


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