The Worms Beneath Our Feet:
A study of worm density and its effects on soil organic matter and soil respiration in different
land management sites on the Mount Holyoke College campus
Julia Thurston, Marielena Lima, Erin Pierce
Abstract:
Invasive earthworms can have effects on the organic matter in the soil and the soil
respiration rates. The presence of worms can also indicate soil rich in organic matter. The
amount of soil organic matter depends on what is added to the soil in the form of falling leaves,
decomposing forest detritus or compost through human application. Studying different land
management sites (a predominantly deciduous forest area, a predominantly coniferous forest area,
a mowed field, and the MHC Student Garden) we were able to investigate the differences and
possible relations between worm density, soil respiration and soil organic matter. We measured
worm density with the use of a mustard solution, soil respiration with a CO2 meter, and soil
organic matter by taking soil cores and processing them in the lab. From three plots at each of
our four sites we used ANOVA and t-tests to find that there is a statistically significant higher
mean density of worms in the garden site than in the other three sites. We did not find any
significant relationships between worm density and soil organic matter or worm density and soil
respiration. Our results suggest that worms prefer soils that are well aerated. Future studies could
investigate relationships between worm density and bulk soil density.
Introduction:
Earthworms have a unique relationship with soils in the northeast and can be biological
indicators of soil health. When they burrow they aerate the soil through movement. Worms bring
organic material into the soil by eating plant detritus, breaking down the nutrient compounds,
and then excreting that material in a form called castings (Raven et al 2012). However,
increased worm activity and abundance can also be detrimental to the amount of soil organic
matter (SOM) in the soil. The fact that they process nutrients from plant litter, makes them
easily accessible for living plants, thus not allowing the SOM to build up in the soil (Bohlen et al.
2004). If there are earthworms in the soil the soil likely has a relatively high level of SOM, but it
does not necessarily mean that the worms make the soil healthy. Worms are attracted to soils
with SOM and thus worm density can be an indicator of soil health (Grossman 2013).
Worms also contribute to soil ecosystems by increasing respiration rates. Soil respiration
releases carbon from the soil into the atmosphere. An experiment studying the competitive
relationship between the invasive earthworms and the native North American millipedes in red
oak and eastern hemlock littered soils showed that earthworms increased respiration in both the
soils. The researchers suggested that widespread invasion of earthworms would cause a net loss
of carbon due to this increased respiration (Snyder et al. 2009). In our study, we investigated
how different levels of management (forests, field, and garden) influence worm density and how
worm density may influence soil organic matter content. We measured the percent of soil that is
organic material, and measured soil respiration in terms of CO2 content in ppm.
Our study could form the basis of reassessing land management practices here on the
Mount Holyoke campus. Since worms can be biological indicators of soil health, the study may
point to areas where the soil could be amended or managed differently. For example, in a study
conducted in the Republic of Moldova, researchers collected data on worm density, depth, and
biomass in the soil among different field agro-ecosystems. Their study concluded that at sites
with more biomass, the mean density of worms was greater. They concluded that earthworms
can be useful in biological monitoring of soil (Andriuca et al. 2012). In this same way, we can
use worm density data on the Mount Holyoke campus to assess land management impacts on soil.
We investigated how worm density correlates with soil respiration and soil organic matter
in different sites: a deciduous forest stand, a coniferous forest stand, the Mount Holyoke student
garden, and an open field on Prospect Hill. We postulated that worm density would be highest in
the predominantly deciduous forest site. At this time of year, deciduous trees are currently
dropping their leaves, which increases the amount of leaf litter on the ground. Worms prefer
habitats where there is a lot of plant detritus to consume, so more leaves will attract more worms.
Additionally, the forest is the least disturbed soil area we tested in terms of human traffic, and
there is relatively minimal use of chemicals and landscaping. We also hypothesized that areas of
high worm density will have a higher soil respiration. Worms breathe in oxygen and breathe out
carbon dioxide, so more worms in the soil will produce more CO2. We think that there will be
more worms where there are greater CO2 levels. Finally we predict areas of high worm density
will have more soil organic matter (SOM) than areas of low worm density. Worms feed on
organic matter in soil, therefore if there is a high density of worms, there will be a high density
of soil organic matter.
Site Description:
Data was collected from four different sites on the Mount Holyoke College Campus in
South Hadley, MA. All the testing sites are located on Wethersfield fine sandy loam soil (NRCS
2013) and samples were collected on a relatively flat slope at each site. The first site is the
mowed field on Prospect Hill behind Mandelle Hall (42°15'9.68"N, 72°34'14.99"W) (Google
Earth 2009). The field has minimal leaf coverage with a thick grass and vegetative cover. The
second site is the predominantly coniferous forest on Prospect Hill (42°15'8.33"N,
72°34'13.60"W). The forest consisted of mostly coniferous and a few deciduous trees, so there
was some leaf cover and tree roots within the soil. The third site is the MHC Student Garden
located on top of Prospect Hill (42°15'9.23"N, 72°34'8.93"W). The Student Garden consists of
six plots amended with either organic fertilizer or organic compost. The plot we sampled is
supplemented with organic fertilizer, tilled yearly, has minimal leaf cover, and has relatively
uncompressed soil (Kayla Smith, personal communication 2013). The garden was fallow at the
time of the collection; some tomatoes from the summer crop were decomposing in the plot. The
final site is the predominantly deciduous forest on Prospect Hill (42°15'11.91"N,
72°34'10.69"W). There was substantial leaf coverage and uncompressed soil. There was light
snow accumulation (less than one centimeter) on the day when we sampled this site.
Methods:
During mid to late November 2013, we collected data from four different sites on the
Mount Holyoke College campus in South Hadley, MA: a predominantly deciduous forest area, a
predominantly coniferous forest area, a mowed field, and the MHC Student Garden. We
collected one sample from each 1ft2 (929cm2) plot for a total of 3 samples at each 25m2 site,
making sure that the slope of each sample site was as level as possible.
In the field, we randomly selected and marked off a 1 square foot plot with a quadrat and
removed any leaf cover from the area. We measured soil temperature using a thermometer in the
soil 10 cm deep, taking the temperature at the first stabilization. Next, we measured soil
respiration by placing a chamber covering the surface of the soil inside the quadrat and placing
the CO2 meter into an opening of the chamber to measure only the CO2 output from the soil and
not the surrounding air. We waited 30 seconds until the meter stabilized, then recorded the
output. Next, we took a 10 cm deep soil core from the soil within the quadrat and placed it in a
Ziploc bag.
To draw worms out of the soil, we prepared a mustard solution consisting of 4 liters of
water and about ⅓ cup of mustard seed for each sample plot and stirred the solution well. We
poured half of the mustard solution over the plot, waited two minutes, and poured the other half
of the solution and waited 10 more minutes. The solution irritates the skin of the earthworms, so
they come to the surface of the soil to escape the solution. We then performed a simple count of
all worms that emerged.
In the lab, we calculated the percentage of soil organic matter (SOM) for all 12 of our
samples. We weighed the empty crucibles and then weighed the crucibles filled ⅔ with the soil
sample. The crucibles with the wet soil were placed in the drying oven to rid the samples of all
water for a total of 24 hours. We removed the crucibles from the drying oven and weighed the
crucibles with the dry soil. We then placed the crucibles in the muffle furnace to burn off the
SOM for four hours and left to cool in the desiccator for one hour. Next, we weighed the
crucibles and calculated percent SOM using the following formula:
% SOM = ((weight of dry soil-weight of ashed soil)/ weight of dry soil) x 100
After compiling our data, we ran ANOVAs, T-tests, and regression analyses at a confidence
level of 0.05 using Excel to analyze the significance of our findings.
Results:
The garden site has the highest mean density of worms with a mean of 3 worms per foot
squared (Figure 1). Results from an ANOVA single factor test concluded that there were
significant differences in sites in terms of worm density (p-value= 0.0005, Table 1). Post hoc ttests showed that the mean worm density was significantly higher in the garden than the
deciduous forest (p-value=0.0152, Table 2), the garden had more worms than the coniferous
forest (p-value=0.0152, Table 3), and the garden had higher worm density than the open field site
(p-value=0.0198, Table 4). Deciduous forest and coniferous forest did not have significantly
different worm densities (p-value=1.0, Table 5). Deciduous forest and open field were also not
significantly different (p-value=0.5185, Table 6). Worm densities in open field and coniferous
forest were also not significantly different (p-value=0.5185, Table 7).
The average CO2 level is greatest in the deciduous forest site, with a mean concentration
of 915.6667 ppm (Figure 2, Table 8). However, results from an ANOVA single factor test
concluded that there was no statistically significant difference between the four sites (p= 0.1879,
Table 8). There is no significant linear relationship between soil respiration and worm density
(p= 0.3281, Figure 3, Table 9).
In terms of SOM, there was no statistically significant difference between the sites (p=0.0983,
Table 10). General trends indicate that the deciduous forest had the highest soil organic matter
content (Figure 4). Regression analysis revealed no significant correlation between soil organic
matter and worm density (p-value=0.2131, Table 11, Figure 5).
Discussion:
We reject the null hypothesis that land management sites have no effect on worm
densities. However, our hypothesis was incorrect as well, since the garden had the highest mean
worm density rather than the deciduous forest. From what we know of the garden plots we can
say that organic matter, manure and plant compost, have been applied to the garden to increase
the humus layer and improve the soil for plant growth (Kayla Smith 2013, personal
communication). A second difference in the garden plot is that the soil was bare at the time of
our sample. There is no vegetation growing in the soil other than a few decomposing plants from
last summer's crop. A third difference is that the soil is relatively loose due to yearly tilling;
students till the garden so that plants can grow each season. These three key differences provide
an explanation as to why mean worm density was highest in the garden. First, the soil is
guaranteed to have organic matter applied to it and thus makes for a great environment and food
source for worms. Worms will be attracted to this site because soil organic matter will never be
depleted since it is supplemented each year. Second, since the soil is mostly bare and relatively
loose, the mustard solution sunk into the soil more than at the other three sites. At the deciduous,
coniferous, and field sites we observed that much of the solution was running off out of the plot
down the slight slope on which our sites were located. In these sites less solution was able to
sink into the soil and irritate the worms as compared to the garden. Therefore, more worms
would emerge from the site where the most mustard solution could sink in: the garden.
Carbon is a fundamental element in our lives and is stored in oceans, plants, and soil. It
combines with oxygen to form carbon dioxide, one of the two forms of carbon in the atmosphere
and a gas that most living organisms respire (Raven et al 2012). About 20% of global carbon
dioxide emissions originate through root, microbial, and faunal respiration in the soil (Rastogi et
al. 2002). In our study mean soil respiration is greatest in the site with one of the lowest mean
worm densities. These results contrast the previous work done by Speratti and Whalen in 2007,
which reported high earthworm density resulted in greater carbon dioxide emissions compared to
areas of low earthworm density. This suggests that there are factors other than worm density
playing a role in soil respiration. A possible explanation is that other living organisms in the
deciduous forest were contributing high levels of carbon dioxide, as we did observe spiders
crawling out of the plots. Another possibility is that invading earthworms could have been
introduced to the deciduous forest more recently than the other sites. Studies report that CO2
emissions increase due to earthworms in the short-term, because they accelerate decomposition
and sequester carbon, but over time the total amount of carbon loss decreases and eventually
disappears (Lubbers et al 2013).
Soil respiration is an influential factor in global climate change today. Carbon dioxide is
a heat-trapping greenhouse gas that has been increasing in the atmosphere due to human activity
(IPCC 2007). Human activity, such as using worms as bait, introduce invasive earthworms into
new environments. These earthworms can impact carbon dynamics through their activities. If
earthworms sequester carbon from the soil, more CO2 enters the atmosphere, enhances the
greenhouse effect, and contributes to global warming.
One potential source of error from data collection is that we used two different CO2
chambers: one transparent cube (173.65 m2) and the other opaque cylindrical trapezoid (351.19
m2). Light can shine through the transparent chamber and plants could photosynthesize during
data collection, reducing the amount of CO2 in the chamber and skewing our results.
Additionally, weather varied between data collection days. We observed snow, sun, temperatures
in the ranges of 50 degrees F, and in the range of 30 degrees F. Future studies could eliminate
differences in weather by sampling all in a single day. Repeating this study in the spring could
also provide different results; earthworms hibernate in the winter (Groffman 2013 personal
correspondence). Since our data suggest that worms prefer more aerated soils like the soil in the
student garden, future studies could investigate a possible correlation between bulk density of the
soil and worm density. More long-term studies need to be done to expand our knowledge on the
effects of invasive earthworms on soil respiration because of the important information it can
provide us about soil health and climate change. On a broad scale, it is important to have healthy
soils because they serve as a basis for resistance to the impending climate change that the earth
faces. Plants are able to grow better in healthy soils and climate change may put stress on plants;
thus it is important to have good soil so as to combat climate change effects.
Conclusion:
We found that there was a statistically significant difference in worm density in different
land management sites. The differences that we found in soil respiration and the differences in
soil organic matter across the different land management sites were statistically insignificant.
We found no significant relationship between worm density and soil organic matter, nor did we
find a significant relationship between worm density and CO2. Future studies could investigate
other factors that contribute to worm density, such as bulk density, vegetative cover, or season.
Literature Cited:
Andriuca, Valentina, Daniela Girla and Madalina Iordache. 2012. Comparative Earthworm
Research in Various Ecosystems with Different Anthropic Impact. Research Journal of
Agricultural Science, 44 (3).
Bohlen, Patrick J., Stefan Scheu, Cindy M Hale, Mary Ann McLean, Sonja Migge, Peter M
Groffman, and Dennis Parkinson. 2004. Non-native invasive earthworms as agents
of change in northern temperate forests. Front Ecol Environ, 2(8): 427–435.
Google Inc. (2009). Google Earth (Version 5.1.3533.1731) [Software].
Groffman, Peter. 2013. Environmental Science 200 Guest Lecture. Mount Holyoke College
IPCC, 2007: Climate Change 2007: The Physical Science Basis. Contribution of Working Group
I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change
[Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and
H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA, 996 pp.
Lubbers I. M., K. Jan van Groenigan, S. J. Fonte, J. Six, L. Brussaard, and J. Willem van
Groenigan. 2013. Greenhouse-gas emissions from soils increased by earthworms. Nature
Climate Change, 3(3): 187-194
Natural Resources Conservation Service. “Web Soil Survey.” Last Modified February 15, 2013.
http://websoilsurvey.sc.egov.usda.gov/App/HomePage.htm
Rastogi, M., S. Singh, H. Pathak. 2002. Emission of carbon dioxide from soil. Curr. Sci. 82: 510518.
Raven et al. 2012. Ecosystems and the Physical Environment, Page 59 in Environment. 8th
Edition. John Wiley & Sons, Inc. Hoboken, NJ.
Raven et al. 2012. Soil Resources, Pages 287-304 in Environment. 8th Edition. John Wiley &
Sons, Inc. Hoboken, NJ.
Snyder, Bruce A., Bas Boots and Paul F. Hendrix. 2009. Competition between invasive
earthworms (Amynthas corticis, Megascolecidae) and native North American millipedes
(Pseudopolydesmus erasus, Polydesmidae): Effects on carbon cycling and soil structure.
Soil Biology and Biochemistry, 41:1442-1449.
Speratti, A. B. and J. K. Whalen. 2007. Carbon dioxide and nitrous oxide fluxes from soil as
influenced by anecic and endogeic earthworms. Applied Soil Ecology, 38: 27-33.
Tables and Figures:
Table 1. ANOVA Single Factor test of worm density across sites.
Anova: Single
Factor
SUMMARY
Groups
Field
Coniferous
Garden
Deciduous
Count
Sum
3
3
3
3
2
1
9
1
Average
Variance
0.666666667
0.333333333
3
0.333333333
0.333333333
0.333333333
0
0.333333333
standard
error
0.333333333
0.333333333
0
0.333333333
ANOVA
Source of Variation
SS
Between Groups
Within Groups
14.91666667
2
3
8
Total
16.91666667
11
df
MS
F
P-value
4.972222222
0.25
19.88888889
0.000457469
Table 2. Post hoc t test of worm density between deciduous forest and garden.
t-Test: Two-Sample Assuming Unequal Variances
Deciduous
Garden
Mean
Variance
Observations
Hypothesized Mean Difference
0.333333333
0.333333333
3
0
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail
2
-8
0.007634036
2.91998558
0.015268072
4.30265273
3
0
3
Table 3. Post hoc t test of worm density between coniferous forest and garden.
t-Test: Two-Sample Assuming Unequal Variances
Garden
Mean
Variance
Observations
Hypothesized Mean Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail
3
0
3
0
2
8
0.007634036
2.91998558
0.015268072
4.30265273
Coniferous
0.333333333
0.333333333
3
F crit
4.066180551
Table 4. Post hoc t test of worm density between open field and garden.
t-Test: Two-Sample Assuming Unequal Variances
Garden
Mean
Variance
Observations
Hypothesized Mean Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail
3
0
3
0
2
7
0.009901971
2.91998558
0.019803941
4.30265273
Field
0.666666667
0.333333333
3
Table 5. Post hoc t test of worm density between deciduous forest and coniferous forest.
t-Test: Two-Sample Assuming Unequal Variances
Mean
Variance
Observations
Hypothesized Mean Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail
Deciduous
0.333333333
0.333333333
3
0
4
0
0.5
2.131846786
1
2.776445105
Coniferous
0.333333333
0.333333333
3
Table 6. Post hoc t test of worm density between deciduous forest and open field.
t-Test: Two-Sample Assuming Unequal Variances
Mean
Variance
Observations
Hypothesized Mean Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail
Deciduous
0.333333333
0.333333333
3
0
4
-0.707106781
0.259259259
2.131846786
0.518518519
2.776445105
Field
0.666666667
0.333333333
3
Table 7. Post hoc t test of worm density between coniferous forest and open field.
t-Test: Two-Sample Assuming Unequal Variances
Coniferous
0.333333333
0.333333333
3
0
4
-0.707106781
0.259259259
2.131846786
0.518518519
2.776445105
Mean
Variance
Observations
Hypothesized Mean Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail
Field
0.666666667
0.333333333
3
Table 8. ANOVA single factor test of CO2 concentration among sites.
Anova: Single
Factor
SUMMARY
Groups
Count
Field
Coniferous
Garden
Deciduous
3
3
3
3
Sum
Average
Variance
1212
1631
1440
2747
404
543.6666667
480
915.6666667
511
162.3333333
63
303946.3333
Standard
Error
13.0511813
7.356025497
4.582575695
318.3008709
df
MS
F
P-value
F crit
154832.1111
76170.66667
2.03269996
0.187915079
4.066180551
ANOVA
Source of
Variation
Between Groups
Within Groups
464496.3333
609365.3333
3
8
Total
1073861.667
11
SS
Table 9. Regression analysis of worm density and CO2 concentration.
SUMMARY
OUTPUT
Regression Statistics
Multiple R
0.309192
R Square
0.0956
Adjusted R
0.00516
Square
Standard
311.6409
Error
Observation
12
s
ANOVA
df
Regression
1
Residual
10
Total
11
Intercept
Worms
Coefficient
s
670.2266
-77.9015
SS
MS
F
102661.
2
971200.
5
107386
2
102661.
2
97120.0
5
1.05705
4
Standar
d Error
121.783
2
75.7699
6
t Stat
P-value
5.50344
2
1.02813
0.00026
1
0.32811
4
Significanc
eF
0.3281142
7
Lower
95%
398.87678
7
246.72746
8
Upper
95%
941.576
4
90.9245
1
Lower
95.0%
398.876
8
246.727
Upper
95.0%
941.576
4
90.9245
1
Table 10. ANOVA single factor test of SOM percentage among sites.
Anova:
Single
Factor
SUMMARY
Groups
Count
Field
Coniferous
Garden
Deciduous
3
3
3
3
Sum
Average
Variance
5.52939422
8.251467165
5.069611423
11.99225755
1.843131407
2.750489055
1.689870474
3.997419184
0.16831703
1.158534722
0.020623505
3.225499817
Standard
Error
0.236866369
0.62143241
0.082912615
1.036902409
df
MS
F
P-value
F crit
2.950435985
0.098262647
4.066180551
ANOVA
Source of
Variation
Between
Groups
Within
Groups
10.11920266
3
3.373067554
9.145950148
8
1.143243769
Total
19.26515281
11
SS
Table 11. Regression analysis of SOM and worm density.
SUMMA
RY
OUTPUT
Regression Statistics
Multiple
0.387685
R
489
R Square 0.150300
038
Adjusted
0.065330
R Square
042
Standard 1.198919
Error
973
Observati
12
ons
ANOVA
df
Regressi
on
Residual
10
Total
11
Intercept
SOM
1
Coefficie
nts
2.017065
422
0.363287
716
SS
MS
F
2.542575
651
14.37409
102
16.91666
667
2.542575
651
1.437409
102
1.768860
131
Standard
Error
0.782735
781
0.273151
737
t Stat
P-value
2.576942
91
1.329985
011
0.027560
466
0.213059
789
Significa
nce F
0.213059
789
Lower
95%
0.273021
417
0.971907
713
Upper
95%
3.761109
426
0.245332
281
Lower
95.0%
0.273021
417
0.971907
713
Upper
95.0%
3.761109
426
0.245332
281
3.5
b
Mean Worm Density
3
p-value=0.0005
2.5
2
1.5
a
1
a
a
0.5
0
Field
-0.5
Coniferous
Garden
Deciduous
Figure 1. Mean worm density among sites +/- 1 SE. Different letters above bars indicate
significant differences between means. Repeated letters indicate no significant difference in
means.
1400
1200
a
p-value=0.1879
CO2 (ppm)
1000
800
600
a
a
a
400
200
0
Field
Coniferous
Garden
Deciduous
Figure 2. Mean CO2 concentration among sites +/- 1 SE. Different letters above bars indicate
significant differences between means. Repeated letters indicate no significant difference in
means.
CO2 (ppm)
1800
1600
1400
1200
1000
800
600
400
200
0
y = -77.901x + 670.23
R² = 0.0956
p-value=0.3281
0
0.5
1
1.5
2
Worm Density
2.5
3
3.5
Mean Soil Organic Matter
(%)
Figure 3. Linear regression of carbon dioxide concentration and worm density.
6
p-value=0.0983
a
5
4
3
a
a
a
2
1
0
Field
Coniferous
Garden
Deciduous
Figure 4. Mean soil organic matter content (%) +/- 1 SE. Different letters above bars indicate
significant differences between means. Repeated letters indicate no significant difference in
means.