Download The effects of winter moth defoliation on forest growth and

The effects of winter moth defoliation on forest growth
and production inferred from satellite imagery and
dendrochronology
Erin Gleeson, Rhodes College
2000 North Parkway, TN 38112
Co-authors: Christopher Neill and Greg Fiske
Woods Hole Research Center
149 Woods Hole Road, Falmouth, MA 02540
Gleeson 1
Abstract
Forest disturbances are events that can cause change in the structure and composition of a
forest ecosystem. Insect outbreaks may be a consequence of climate change, and could create
unexpected dynamics in nature. Recently, and invasive pest from Europe, called the winter moth,
has invaded Massachusetts and most of New England. The winter moth causes widespread
defoliation by stripping the leaves off of all deciduous trees. I attempted to use remote sensing
satellite data from MODIS, to classify sites that had experienced heavy defoliation and sites that
had experienced little to no defoliation. Then, by looking at radial increment growth in tree
cores, I created estimates of forest biomass growth, which I used as a model to try and study the
effects of winter moth defoliation on greater areas of land. I found that defoliation from the
winter moth has a large effect on tree ring width and overall tree growth because of how time
period (pre and post winter moth) at each treatment affected ring width increment. The winter
moth also reduced carbon storage in southeastern Massachusetts by around 51%. Clearly there
are serious implications for an insect outbreak like this one, and measures, such as biological
control by releasing natural parasitic enemies of the winter moth are being utilized. Climate
change and a shift towards warmer global temperatures are predicted to increase the spread and
severity of winter moth defoliation, and it is important that we think about future studies, and
how we can control the reintroduction and spread of invasive insects that cause so much harm to
ecosystem services and native ecosystem dynamics.
Introduction
Forest disturbances are widespread and cause pronounced changes in different
ecosystems. Disturbances take many forms, and often have consequences on the ecosystem
services that forests provide. Ecological disturbances may reduce tree growth, and in turn affect
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carbon storing capabilities of the forest. Typically, disturbance events result in a net reduction in
ecosystem carbon stocks. They alter how fixed carbon is allocated, whether it is directly released into the
atmosphere, or stored in woody biomass, and they influence species composition and ecosystem structure
(Williams et al 2016). Carbon sequestration is a crucial ecosystem service that our forests provide.
Forests are carbon sinks, and increases in woody biomass directly increases the amount of
carbon that is sequestered by the forest. Nutrient cycling in these systems may also be impacted
by defoliation from the winter moth. Lovett et al. (2006) suggests that insect infestations such as
winter and gypsy moth defoliations produce an increase in stream water nitrate concentrations.
This influx of nitrogen in highly defoliated areas most likely comes from increased water
drainage and leaching from damaged foliage (Lovett et al. 2006). Healthy hardwood trees
usually recover and produce new leaves after winter moth outbreaks, however, after multiple
years of defoliation and added stress, like drought, the winter moth can contribute to widespread
mortality of trees.
Multiple factors including natural disturbances, like fire, as well as human caused insect
introductions, can decrease the amount of biomass in a forest and turn it into an atmospheric
carbon source (Jacquet et al. 2012). On a large scale, these growing carbon sources have the
potential to perpetuate global warming and climate change by increasing carbon dioxide
concentrations in the atmosphere. The recurrent introduction of invasive insects is one of the
most serious ecological threats to United States forests. These invasive pests are an undesirable
repercussion of international trade and travel, and they are responsible for widespread ecological
and economic damage (Lovett et al. 2016). Global warming and insect outbreaks can create a
positive feedback loop, where warmer average temperatures trigger large-scale outbreaks of
insect defoliators, which in turn increases overall tree mortality (Jacquet et al. 2012). It is
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imperative that we examine the impact of defoliation on overall tree growth, so that we can
address the potential long term effects of these invasive insect outbreaks on global climate
change and overall forest health.
Northeastern terrestrial forests have been host to many different invasive species. One of
these exotic pests, the winter moth (Operophtera brumata), is native to Europe, and was
identified in Massachusetts around 2003, however, there is speculation that the winter moth has
been present since the 1990s (Simmons et al. 2014). Specifically, the winter moth invaded
Falmouth, MA in 2007 (Hibbard and Elkinton 2015). The winter moth caterpillar is known for
defoliating native deciduous trees such as oak, and maple in the early summer months between
late May and mid-June. Their larvae feed on the expanding buds and later on the foliage for
approximately six weeks, effectively removing the photosynthetic tissue that is critical for plant
maintenance and growth (Hibbard and Elkinton 2015). Then, the adult moths emerge from the
soil during the winter months of November and December for mating purposes. Other than
Massachusetts, the winter moth has invaded most of New England, Nova Scotia, and even
Washington state and Oregon.
Dendrochronology, the analysis of annual tree rings, is an effective tool for studying
invasive insect outbreaks. Trees that are defoliated by the winter moth have to expend more
energy to re-grow the leaves that they lost, so the radial growth observed in a tree core should be
smaller in years with high winter moth infestation. Defoliation from winter moths is damaging to
these forests because it decreases radial growth and basal area of the trees, which can be used as
a predictor for tree mortality, and tree production and carbon sequestration decline. Increases in
tree mortality may also alter the species composition of deciduous forests by creating gaps in the
canopy that allow early successional species like grasses and shrubs to establish and grow
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(Simmons et al. 2014). Measuring tree diameter increment is a proxy used for whole tree growth,
and is self-scaling because while large trees produce more biomass than small trees, a specific
diameter increment represents more absolute biomass in a large tree than in a small tree
(Bowman et al. 2013). Reducing radial tree growth could cause a measurable reduction in carbon
storage, because trees store carbon, and sequester it as they grow (Nowak et al. 2012).
Kulman (1971), states that the effects of winter moth defoliation on tree growth can be
detected with a “horizontal sequencing mode” of observing the differences in thickness of the
tree rings in a tree core. Defoliation not only has an effect on radial tree growth, but also overall
tree productivity. Outbreaks from defoliating insects are known as ephemeral forest disturbances
that are short lived, and often allow the forest recovers quickly within the same growing season
(De Beurs and Townsend 2008). Defoliation causes a decrease in leaf area index (LAI), which,
in turn, decreases the amount of chlorophyll, the tree’s photosynthesizing machinery. Because
changes in LAI and leaf chlorophyll together make up the measure of vegetation canopy
“greenness,” that can be seen clearly from satellite imagery, and “greenness” is commonly used
to monitor the Earth’s vegetation cover from space (Jiang et al. 2008). Remote sensing
techniques are a useful way to map the occurrence of defoliation, and also the level of severity
(De Beurs and Townsend 2008). MODIS, or moderate resolution imaging spectroradiometer, is
an instrument aboard the Terra and Aqua satellites. The Terra and Aqua satellites where MODIS
is present, view the Earth’s surface every one to two days. MODIS is used in research devoted to
understanding global processes, and develop models to assist in predicting global (National
Aeronautics and Space Administration 2016). MODIS data has course special resolution which
is more effective in mapping large-scale vegetation changes, and the data is available and
updated daily (De Beurs and Townsend 2008).
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. In this study I attempt to answer three questions: 1) Can we use remote sensing
techniques to estimate areas of the forest have been severely affected by defoliation from the
winter moth? 2) What can remote sensing and dendrochronology (tree ring dating) tell us about
how defoliation from the winter moth affects woody biomass growth? 3) How does defoliation
from the winter moth affect overall carbon storage in northeastern forests? I was interesting in
using these techniques to investigate local insect forest disturbances in Massachusetts. In this
study, I attempted to test MODIS satellite data by comparing tree growth from two different
changes in the enhanced vegetation index (EVI) since 2000, to see if there was any evidence of
winter moth defoliation, other than what was observed based on the changes in foliar biomass.
Then I want to find the effects that winter moth defoliation would have on the total amount of
carbon stored in large areas of land to get a better idea of the severity of the outbreak and what
the implications are for future northeastern forests that could eventually be affected by the winter
moth.
Materials and Methods
Sampling Sites
I identified treatments using MODIS satellite imagery to determine areas of Barnstable
county that had experienced heavy defoliation or little to no defoliation. Then, based on these
two treatments, I found twelve different sampling sites, six of these sites had experienced heavy
defoliation from the winter moth since 2000, while the other six had experienced little to no
defoliation from the winter moth since 2000. I paired the appropriate treatment level to each of
the twelve sites by using a Mann-Kendall trend statistic, which assigned a numerical value to
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each randomly generated point across Barnstable County. The values at each point represented
the enhanced vegetation indices (EVI), which is a measure of vegetation canopy “greenness,”
leaf area, and canopy cover, that simultaneously corrects for some distortions in the reflected
light caused by the particles in the air as well as the ground cover below the vegetation (Jiang et
al. 2008). The Mann- Kendall statistic generates indices of “greenness” by utilizing imagery
from the MODIS satellite to identify areas of high and low levels of defoliation. This statistical
test compares bin values, also known as categories, from an initial time period to a sequential
time period. The result for each pair of time periods compared are summed, and an expected sum
of zero indicates no trend in the values over time. If the first is smaller than the second, the
result are greater than zero, which indicates an increase in “greenness” as a proxy for growth.
However, if the first is larger than the second, the result is less than zero, which indicates a
decrease in “greenness.” The MODIS satellite imagery and EVI values that I utilize compare
defoliation on an annual timescale starting from 2000 to present day, and only between the
months of late May to early June when the winter moth caterpillar outbreaks occur. The
sampling sites that have not experienced heavy defoliation are from the Quashnet Woods State
Reservation and Wildlife Management Area, the Kettle Holes Conservation Area, and the John’s
Pond Conservation Area. Together, these three areas make up approximately 669 acres of
forested land that is unaffected by the winter moth. The sampling sites that have experienced
heavy defoliation from the winter moth include Beebe Woods, and the Long Pond Watershed,
which make up approximately 1,040 forested acres.
After identifying these twelve sites, I used vector data of protected and recreational open
space from the MassGIS database, along with trails mapped by the 300 Committee Land Trust to
find potential sampling sites. I chose sites based on accessibility and proximity to the trail in
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each area, and I used a GPS to find each site based on the latitude and longitude of the points in
ArcGIS.
At each of these twelve sites, I cored five different oak trees at diameter at breast height
(DBH) within a 20-meter by 20-meter plot around the latitude and longitude coordinates from
the Mann-Kendall statistically generated points, and recorded the species name and DBH. I also
created two random 20-meter by 20-meter plots at Beebe Woods, Long Pond Watershed, Kettle
Holes Conservation Area, th Quashnet Woods State Reservation and Wildlife Management Area,
and John’s Pond Conservation Area. In these randomly chosen plots, I identified the species
name, and the DBH of all the live oak and pine trees present within the 20-meter by 20-meter
area.
Dendrochronology
I used a Zeiss Axio Zoom.V16 fluorescence stereo zoom microscope to examine and date
the rings in the cores that I collected. This microscope allowed me to measure the ring width, or
the radial increment of each year in the core from 2000 to 2016 to the micron. Ring width
corresponds to the amount of growth for that individual tree in a given year, which can be used
to create assumptions about the weather and other external factors that would have affected the
radial growth of the tree. Thicker rings in the core indicate that greater amounts of growth for the
tree than thinner rings. I compared my observations of yearly tree growth from the radial
increment of the cores across each treatment site. With these measurements I made inferences
about total growth for the sampled forested area that was show to be affected or unaffected by
defoliation from the winter moth in the remote sensing data, and the overall effects of defoliation
on growth and carbon sequestration at each treatment site.
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Data Analyses and Scaling
To estimate tree biomass and annual growth increment for my sixty cored trees, I used
equations from terrestrial labs #1 and #2, to find the basal area, total wood biomass, wood
biomass increment growth per year, and percent biomass increase for every year from 2000 to
2016 in each tree. I found the basal area, the cross sectional area of tree trunks at breast height
per hectare, of every year from 2000-2016 in the sixty trees that I cored, as well as for all of the
trees in every 20-meter by 20-meter plot in each forested area that I sampled in. Basal area is
calculated from tree diameter at breast height and the area of a circle (
𝐷𝐵𝐻 2
2
) × 𝜋. Using the
measured radial increment from each year in every core, I found the yearly wood biomass
growth in all sixty cored trees. I calculated yearly growth by applying allometric equations from
Whittaker and Woodwell (1968), that are specific to each tree species. The equation for total
aboveground woody biomass of individual trees is:
𝑙𝑜𝑔10 𝑌 = 𝑎 + 𝑏 × 𝑙𝑜𝑔10 𝐷𝐵𝐻
Y is the total aboveground biomass, and a and b are species specific intercept and slope
of the linear equation derived from dimensional analysis of the above-ground dry weight of
forest-grown trees. To find wood biomass growth per year, I subtracted the total wood biomass
of the previous year from the current total wood biomass.
To scale up these growth rates, I used the basal area from the cored trees and the plots
where I sampled DBH, to find the change in woody biomass per hectare. I used dimensional
analysis to determine the growth in wood biomass for the total area of the 20-meter by 20-meter
density plots in kilograms per hectare. The equation for the growth in wood biomass in grams
per hectare is:
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(𝒈𝒓𝒐𝒘𝒕𝒉 𝒐𝒇 𝒄𝒐𝒓𝒆𝒅 𝒕𝒓𝒆𝒆𝒔 (
𝒈𝒓𝒂𝒎𝒔
𝒄𝒎𝟐
𝒄𝒎𝟐
) ÷ 𝒃𝒂𝒔𝒂𝒍 𝒂𝒓𝒆𝒂 𝒐𝒇 𝒄𝒐𝒓𝒆𝒅 𝒕𝒓𝒆𝒆𝒔 𝒇𝒐𝒓 𝟏, 𝟔𝟎𝟎𝒎𝟐 (
)) × 𝒃𝒂𝒔𝒂𝒍 𝒂𝒓𝒆𝒂 𝒐𝒇 𝒅𝒆𝒏𝒔𝒊𝒕𝒚 𝒑𝒍𝒐𝒕𝒔 𝒑𝒆𝒓 𝒉𝒆𝒄𝒕𝒂𝒓𝒆 (
)
𝒚𝒆𝒂𝒓
𝒚𝒆𝒂𝒓
𝒚𝒆𝒂𝒓
To find the annual change in wood biomass, I multiplied the annual change in wood
biomass from the tree cores by the annual basal area of those cored trees. Then I divided this by
the annual basal area of the 20 meter by 20 meter plots. I converted the total basal area to the
annual basal area from the 20 by 20 meter plots from 2000-2016 by multiplying the total basal
area by the basal area of the cored trees from that particular year divided by the basal area of the
cored trees from that previous year. I used this annual change in wood biomass as a measure of
the rate of growth of the areas where I sampled, and I compared these growth rates across
treatments of heavy defoliation versus sites that had experienced little to no defoliation. I also
compared these growth rates for year pre and post winter moth infestation. I used the values of
percent carbon of woody biomass from the semester in environmental science Terrestrial
Primary Productivity Lab Week 2 data. We found that 44% of woody biomass was made up of
carbon, and I was able to use this percentage as a conversion factor to calculate the amount of
carbon in the woody biomass of the forest.
Results
Total radial increment growth decreases from pre-winter moth years (2000-2007) to post
winter moth years (2008-2016) at the heavily defoliated sites. At the sites that experienced little
to no defoliation, radial increment growth actually increased from pre-winter moth years to postwinter moth years (Figure 1). We ran an analysis of variance for the different defoliation
treatments, and for pre and post winter moth time periods, as well as the interaction between
treatments and time period to see if they were significant influences on ring width (radial
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increment growth). Radial increment growth between treatments that experienced heavy
defoliation and little to no defoliation is statistically significant. The relationship between tree
ring width and treatment (defoliated or little to none) significantly differed by period, revealing
that defoliation has a large effect on tree ring width and overall tree growth.
The overall rate of woody biomass growth for one hectare of heavily defoliated forest
decreases, while the rate of woody biomass growth for one hectare of forest that has experienced
little to no defoliation slightly increases (Figure 2). These two trends start to diverge around the
year 2009. The forested area that is heavily defoliated loses approximately 1.6 metric tons per
hectare of wood biomass over a seventeen year, or 57% of the initial wood biomass from 2000.
Comparatively, for a hectare of forest that has experienced little to no defoliation, 1.16 metric
tons of wood biomass is added per hectare. So, these “unaffected forests” have gained
approximately 15% of the initial wood biomass. The total carbon dioxide sequestered by these
different forests follows a similar trend, forests that have experienced little to no defoliation,
experience an increase of 0.55 tons of carbon per hectare in the amount of carbon fixed, whereas,
heavily defoliated forests actually produce 0.7 metric tons of carbon per hectare (Figure 3).
Figure 4 shows the scaled up change in wood biomass for both defoliation treatments for
the Long Pond Watershed, which is 259 hectares in total area. If the forested area around the
Long Pond Watershed experienced heavy defoliation, then total growth would be 15,369 metric
tons for all 259 hectares. If the forested area around the Long Pond Watershed experienced light
or no defoliation, then total growth would be around 32,168 metric tons for all 259 hectares. The
Long Pond Watershed alone would lose 16,798 metric tons of wood biomass if all of the forested
area had experienced heavy defoliated, rather than little to no defoliation. There is a 48%
decrease in total growth (tonnes) between the heavily defoliated scenario versus the light or no
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defoliation scenario. The total amount of carbon sequestered by the forested area of the Long
Pond Watershed under heavy defoliation is 6,598 metric tons, and the total amount of carbon
sequestered by the forested area of the Long Pond Watershed under little to no defoliation is
13,565 metric tons. The forested area of the Long Pond Watershed under heavy defoliation is
sequestering carbon, however it is only taking 48% out of the atmosphere relative to the forested
area under little to no defoliation (Figure 5).
Figure 6 shows all of the forested area in southern Massachusetts, or Plymouth County,
Bristol County, and Barnstable County from the MassGIS LandUse layer for 2005. I applied
growth rates from the heavily defoliated sites and the sites that experienced little to no
defoliation to the entire area of southern Massachusetts, which was 192,184 hectares of forest.
Figure 7 shows the total amount of carbon sequestered by southern Massachusetts if all of the
forested area experienced heavy defoliation or little to no defoliation. If all of the forested area is
defoliated, then the total amount of carbon sequestered is 0.0048 petagrams per year, compared
to 0.01 petagrams per year of carbon sequestered if all of that forested area experienced little to
no defoliation. There is a loss of around 0.005 petgrams or 51% of carbon lost per year if all of
the forested area in southern Massachusetts is heavily defoliated rather than experiencing little to
no defoliation.
Discussion
From statistical tests in Figure 1, there is a relationship between tree ring width and the
level of defoliation that differed by the period of time when the winter moth is known to be
present. Overall, there is a difference in width caused by time period (pre and post winter moth),
regardless of whether that site experienced heavy defoliation or little to no defoliation. The level
of defoliation controls how much width changes with time period, so ring width decreases with
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an increase in winter moth infestation because of how defoliation decreases or slows radial tree
growth. This data also demonstrates how useful satellite imagery is in this study, because of the
significant difference between tree ring width between the sites that experienced little to no
defoliation versus the sites that experienced little to no defoliation, with the heavily defoliated
sites having less ring width overall as result of winter moth infestation (Figure 1).
Insect outbreaks are a forest disturbance that have a large scale impact on ecosystem
services, specifically the carbon storage capacity of the forest. My results show how carbon
uptake and sequestration slow down as a result of winter moth defoliation. Similarly, Albani et
al. (2010), created a model to predict the mean reduction in the uptake of carbon by eastern
United States forest as the result of another introduced pest, the hemlock wooly adelgid that has
been decimating eastern hemlock trees. This model predicts a reduction of 0.011 petagrams, or
an 8% decrease of carbon as a result of the hemlock wooly adelgid infestation. Albani et al.
(2010) also suggests that northern pine species could increase from 1.2% to 16.3% as a result of
insect defoliation, which could be an interesting project to study in the future. This model is
meant for the entirety of eastern united states forests, so they come to the conclusion that the
small reduction in the uptake of carbon from hemlock woody adelgid infestation is actually
unlikely to have a significant impact on the regional carbon fluxes. My findings for the loss in
carbon sequestration from all of southern Massachusetts were closer to a 50% loss in carbon
sequestration due to defoliation from the winter moth (Figure 7). My estimates seem to be high
in comparison, which could ultimately be due to the fact that I sampled a small area in
comparison to all of southern Massachusetts.
The influx and spread of invasive pests represent a severe risk to United States forests
and landscapes. Specific measures of biological control of the winter moth have been attempted,
Gleeson 13
with the hope that it would take care of the spreading population. Natural parasitic enemies of
the winter moth were collected in France and Germany and considered for release in Nova Scotia
(Elkinton et al. 2014). These parasitoids leave eggs along partially defoliated leaves, where
winter moth larvae ingest the eggs as they feed. This parasite, Cyzenis albicans, was actually
released in Massachusetts and Rhode Island in 2005, and every year after that until 2015. As of
2014, C. albicans is established at 11 sites in the northeastern United States, has achieved
parasitism in excess of 20% at three sites, and appears to have lowered the density of winter
moth at one site. Based on the success of biological control in Nova Scotia and the Pacific
Northwest, principally by the parasitoid, C. albicans, it is highly likely that it will have a similar
effect on winter moth in the northeastern United States (Elkinton et al. 2014). Results of this
attempted biological release are still being monitored, and it will be interesting to see the effect
of this releases in the coming years.
For forest pest insects, it is predicted that general climate warming will affect the
geographical extent and intensity of population outbreaks with potentially severe ecological
consequences (Jepsen et al. 2008). Jepson et al. (2008), makes predictions about the expected
north-eastern outbreak range expansion of the winter moth due to climate warming. They found
that the winter moth’s outbreak range is actually temperature limited, and from the historical
outbreak data, it is clear that the advance of the winter moth outbreaks has occurred gradually,
permitted by a gradual increase in temperature. In response to warmer temperatures, the winter
moth is able to expand its outbreak area further northeast (Jepson et al. 2008). As we look into
the future at how climate change is going to affect forest ecosystems, we need to be weary of the
impacts of disturbances, such as insect outbreaks. We can expect forest dynamics and responses
to disturbance as we generate new ecosystems and new populations of invasive species as a
Gleeson 14
result of changing temperatures and species composition due to climate change. Nonnative forest
insects and pathogens are causing significant ecological and economic damage in the United
States. The ecological damage has included near-extirpation of several important tree species,
shifts in forest composition and ecosystem function, and disruption of wildlife habitat.
Gleeson 15
Figures
Total Radial Increment Growth Pre and Post Winter Moth
Total Radial Increment Growth (cm)
40
35
30
25
Pre-Winter Moth (2000-2007)
20
Post-Winter Moth (2008-2016)
15
10
5
0
Heavy Defoliation
Little to No Defoliation
Figure 1. Total radial increment growth (µm) pre and post winter moth of trees from twelve different
treatment sites, six of which have experienced heavy defoliation, and six that have experienced little to no
defoliation from the winter moth.
Gleeson 16
Forest Biomass Growth Increment Since 2000
Biomass Growth Increment
(tonnes ha-1 yr-1)
9
8
7
6
5
4
Heavy Defoliation
3
Little to No Defoliation
2
1
0
1995
2000
2005
2010
2015
2020
Year
Figure 2. The annual growth per hectare since 2000 from sites that experienced either heavy defoliation,
or little to no defoliation from the winter moth.
Gleeson 17
Change in Annual Carbon Uptake
(tonnes ha-1 yr-1)
Change in Forest Carbon Uptake Since 2000
4
3.5
3
2.5
2
Heavy Defoliation
1.5
Little to No Defoliation
1
0.5
0
1995
2000
2005
2010
2015
2020
Year
Figure 3. The change in the annual carbon uptake by the forest since 2000 from sites that experienced
either heavy defoliation, or little to no defoliation from the winter moth.
Gleeson 18
Biomass Growth in the Long Pond Watershed Since 2000
Total Wood Biomass (tonnes)
35000
30000
25000
20000
15000
10000
5000
0
Long Pond Watershed (heavy defoliation)
Long Pond Watershed (light or no defoliation)
Figure 4. Total growth for all 259 hectares of the Long Pond Watershed if the entire forest experienced
heavily defoliation from the winter moth, versus if the entire forest experienced little to no defoliation.
Gleeson 19
Total Carbon fixed in the Long Pond Watershed Since 2000
16000
Total Biomass Carbon (tonnes/ha)
14000
12000
10000
8000
6000
4000
2000
0
Long Pond Watershed (heavy defoliation)
Total Carbon Fixed (light or no defoliation)
Figure 5. Total biomass carbon for all 259 hectares of the Long Pond Watershed if the entire forest
experienced heavily defoliation from the winter moth, versus if the entire forest experienced little to no
defoliation.
Gleeson 20
0
4
8
16
24
¹
32
Kilometers
Digital Globe, MassGIS
Figure 6. A map showing the total forested area in southeastern Massachusetts from the MassGIS
LandUse layer for 2005.
Gleeson 21
Annual Forest Carbon Uptake
Annual Biomass Carbon
Uptake (PgC/yr)
0.012
0.01
0.008
0.006
0.004
0.002
0
Heavy Defoliation
Little to No Defoliation
Figure 7. Total biomass carbon fixed for all 192,184 hectares of southeastern Massachusetts if the entire
forest experienced heavily defoliation from the winter moth, versus if the entire forest experienced little to
no defoliation.
Gleeson 22
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