Economic Estimates of Feral Swine Damage and Control - Publication

Crop Protection 89 (2016) 89e94

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Crop Protection
journal homepage: www.elsevier.com/locate/cropro

Economic estimates of feral swine damage and control in 11 US states
Aaron Anderson*, Chris Slootmaker, Erin Harper, Jason Holderieath, Stephanie A. Shwiff
USDA/APHIS/WS National Wildlife Research Center, 4101 Laporte Avenue, Fort Collins, CO 80521, USA

a r t i c l e i n f o

a b s t r a c t

Article history:
Received 11 April 2016
Received in revised form
28 June 2016
Accepted 30 June 2016

We report the results of one of the most comprehensive surveys on feral swine (Sus scrofa) damage and
control in 11 US states (Alabama, Arkansas, California, Florida, Georgia, Louisiana, Mississippi, Missouri,
North Carolina, South Carolina and Texas). The survey was distributed by the USDA National Agricultural
Statistical Service in the summer of 2015 to a sample of producers of corn (Zea mays), soybeans (Glycine
max), wheat (Triticum), rice (Oryza sativa), peanuts (Arachis hypogaea), and sorghum (Sorghum bicolor) in
the 11-state region. Producers that failed to respond to the initial mailing received multiple follow-up
phone calls in an attempt to minimize non-response bias, and a total of 4377 responses were obtained. Findings indicate that damage can be substantial. The highest yield loss estimates occur in peanut
and corn production in the Southeast and Texas. Control efforts are common, and producers incur
considerable costs from shooting and trapping efforts. Extrapolating crop damage estimates to the statelevel in 10 states with reportable damage yields an estimated crop loss of $190 million. Though large, this
number likely represents only a small fraction of the total damage by feral swine in the 10 states because
it only includes crop damage to six crops. We hope findings from this survey will help guide control
efforts and research, as well as serve as a benchmark against which the effectiveness of future control
efforts can be measured.
Published by Elsevier Ltd.

Keywords:
Feral swine
Invasive species
Crop damage
Economics
Survey

1. Introduction
Feral swine (Sus scrofa) have become widespread throughout
much of the United States because of their reproductive potential
and adaptable biology (Seward et al., 2004). Over the past 30 years,
the range of feral swine has increased from 17 to 38 states (Bevins
et al., 2014) (Fig. 1). The recent range expansion of feral swine has
inflicted substantial costs on agricultural producers in the United
States. Though estimates of damage to agricultural production
range widely and are largely context specific (Bevins et al., 2014), it
is clear that feral swine have the ability to damage most crops,
transmit diseases to both livestock and other wildlife, and effectively destroy ecosystems (Barrios-Garcia and Ballari, 2012; Crooks,
2002). At the same time, feral swine provide benefits to some in the
form of subsistence and recreational benefits (e.g. hunting), the
latter of which might benefit some agricultural producers (Zivin
et al., 2000). These opposing negative impacts and positive use
values associated with feral swine presence necessitate a better
understanding of their impacts to agricultural producers.

* Corresponding author.
E-mail address: [email protected] (A. Anderson).
http://dx.doi.org/10.1016/j.cropro.2016.06.023
0261-2194/Published by Elsevier Ltd.

While estimates of agricultural damage from feral swine exist,
they are either largely individual (as summarized by Bevins et al.
(2014)), or back-of-the-envelope style aggregations, as in the
widely cited numbers reported by Pimentel et al. (2005). Thus,
there is a need for both a precise and broad understanding of the
how crop damage by feral swine varies across crops and production
regions. This would enhance the efficiency of producer and government led control efforts by allowing resources to be allocated to
the most severe problems. Furthermore, this type of information
could serve as a baseline against which the effects of future control
efforts could be measured. To address this need, the National
Agricultural Statistical Service (NASS) administered a survey instrument that was designed by researchers at the USDA/APHIS/WS
National Wildlife Research Center.
The survey was designed to simultaneously capture information
related to feral swine presence, crop damage, livestock losses,
control methods, live sales, and hunting, but the focus of the present analysis is on crop damage and control efforts. Distribution
targeted producers of corn (Zea mays), soybeans (Glycine max),
wheat (Triticum), rice (Oryza sativa), peanuts (Arachis hypogaea),

90

A. Anderson et al. / Crop Protection 89 (2016) 89e94

Fig. 1. Feral swine distribution in 1982 and 2015.

and sorghum (Sorghum bicolor) in Alabama, Arkansas, California,
Florida, Georgia, Louisiana, Mississippi.
Missouri, North Carolina, South Carolina, and Texas.1 States and
crops were selected by a subjective evaluation of economic
importance (United States Department of Agriculture (2014)),
vulnerability to feral swine (see Fig. 1), and political considerations.
However, the instrument was designed to accommodate responses
for any crop the respondents considered economically important
on their operation. We proceed with a discussion of the survey
instrument, survey distribution, and NASS rules related to disclosure of information. Results are then presented, followed by a discussion of the implications of the findings.

1.1. Methods
Information on crop damage was solicited by the questions
listed inFig. 2. Producers could choose to respond for up to three of
their highest valued crops harvested on their operation in 2014. The
structure of the questions enabled us to capture information from
producers that experienced no crop damage from feral swine so
that we could use the survey results to extrapolate to the statelevel. The questions also go beyond simply soliciting a percentage
yield loss response. Instead, producers were asked how many of the
acres of each crop were damaged by feral swine, as well as actual
yield with the damage and expected yield without the damage on
those acres. Self-reporting wildlife damages the crops is common
and has been shown to be accurate (Conover, 2002; Johnson-Nistler
et al., 2005; Tzilkowski et al., 2002; Wywialowski, 1994).
To calculate feral swine damage to crops, we compared actual
yield reported by each producer to the expected yield reported if no
feral swine damage had occurred. Specifically, each producer reported total acres harvested for each of up to three crops, as well as
average yield per acre, giving total yield. For crop j on producer i’s

1

Sorghum producers were only surveyed in Texas.

operation, this is:

Yieldij ¼ acres harvestedij avg:yield per acreij :

(1)

If some acres were reported damaged by wild pigs, producers
reported: (i) the number of acres damaged, (ii) average yield per
acre on damaged acres, and (iii) expected yield per acre if these
acres had not been damaged. Hypothetical yield losses for each
producer’s crops are then calculated as:

Lossij ¼ acres damagedij avg:yield not damagedij


 avg:yield w=damageij :

(2)

Since actual yield on damaged acres was included in the original
calculation of total yield in (1), hypothetical yield without feral
swine damage is the sum of (1) and (2). Hypothetical yield loss due
to feral swine damage as a percentage of total (hypothetical) yield is
then:

Percent Lossij ¼ 100 

Lossij
:
Yieldij þ Lossij

(3)

Equation (3) gives the portion of yield lost to feral swine damage
at the producer-crop level. To calculate the portion of yield lost for
each crop within each state, we summed yield and hypothetical
loss across all producers of each crop in each state as in (1) and (2),
and used these to calculate the portion of each crop’s yield lost to
feral swine across the state. Along with the producer level responses needed to calculate (3), each producer was given a calculated weight based on a non-response adjustment and Multivariate
Probability Proportional to Size (MPPS) weight, as in Kott et al.
(1998). These weights are used in the calculations that follow,
specifically by weighting each producer’s yields and losses in (1)
and (2) by their unique weight in order to obtain a representative
value at the state level.
To estimate the dollar value of production lost to feral swine
damage for the selected crops at the state level, we must assume

A. Anderson et al. / Crop Protection 89 (2016) 89e94

91

Fig. 2. Feral swine crop damage questions from survey instrument.

that the weights used to account for non-response and farm size
are also applicable to feral swine damage. In other words, we must
assume that the damage experienced by the weighted sample of
observed producers is representative of all producers of the same
crop in their state. Under this assumption, estimated production
value lost to feral swine is the percentage loss by state and crop
from Table 3. For crop j in state s, the calculation of percentage loss
analogous to (3) is:

Percent Lossjs ¼ 100 

Lossjs
:
Yieldjs þ Lossjs

Table 2
Usable observations for calculating percent lost.

Alabama
Arkansas
California
Florida
Georgia
Louisiana
Mississippi
Missouri
North Carolina
South Carolina
Texas

(4)

The dollar value of lost production is then

Percent Lossjs Yieldjs
Lossjs ¼
:
100  Percent Lossjs
Current production value for the selected crops and states were
obtained from NASS Quick Stats for the year 2012 (the most recent
available census year at the time of writing).

Corn

Soybeans

Wheat

Rice

Sorghum

Peanuts

114
44
NA
23
123
32
69
368
202
154
209

121
96
NA
20
63
58
103
404
304
152
45

50
16
NA
NA
23
13
11
97
117
49
230

NA
53
26
NA
NA
16
15
37
NA
NA
39

NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
149

58
NA
NA
51
NA
NA
NA
NA
58
NA
53

Additional questions solicited information on feral swine control efforts (Figs. 3 and 4). Producers were asked about the use of
each method, the cost of each method, and their perceptions about
the effectiveness of each method. Questions about fencing (both

Table 1
Total responses and percent from each state reporting damage and control.

Alabama
Arkansas
California
Florida
Georgia
Louisiana
Mississippi
Missouri
North Carolina
South Carolina
Texas

Responses

Feral swine on land

Crop damage by feral swine

Property damage by feral swine

Attempt to control feral swine

Hunt feral swine

337
202
485
159
386
129
184
674
494
373
954

45%
32%
9%
65%
67%
60%
46%
5%
16%
47%
66%

29%
21%
4%
45%
51%
41%
28%
2%
10%
28%
49%

21%
15%
5%
35%
36%
36%
21%
1%
3%
19%
39%

32%
19%
6%
44%
51%
38%
26%
1%
8%
29%
49%

51%
43%
20%
60%
62%
54%
58%
45%
54%
58%
48%

92

A. Anderson et al. / Crop Protection 89 (2016) 89e94

Table 3
Percent of crop lost to feral swine.

AL
AR
CA
FL
GA
LA
MS
MO
NC
SC
TX

Corn

Soybeans

Wheat

Rice

Sorghum

Peanuts

0.93%
1.09%
NA
4.41%
4.73%
0.83%
1.34%
0%
0.38%
1.59%
1.65%

1.38%
0.27%
NA
3.43%
1.07%
0.74%
0.4%
0.02%
0.09%
1.52%
1.1%

0.62%
0.75%
NA
NA
4.39%
0.94%
0.7%
0.01%
0.15%
1.71%
3.05%

NA
0.27%
0%
NA
NA
1.26%
0.12%
0%
NA
NA
2.46%

NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
2.87%

6.17%
NA
NA
1.84%
NA
NA
NA
NA
0.49%
NA
9.28%

reporting: feral swine on their operation, damage from feral swine
on crops harvested, property damage from feral swine during 2014,
any control methods used to reduce or prevent damage from wild
pigs in 2014, and hunting of feral swine on their operations. Responses from Florida, Georgia, and Texas were most likely to indicate both the presence of feral swine on their land (65%, 67%, and
66% respectively) as well as damage by feral swine (45%, 51%, and
49% respectively). Producers from these three states were also most
likely to attempt to control feral swine, and hunting feral swine was
most common in the Southeast.
Of the responses summarized in Table 1, some observations of
crop-level data were unusable (e.g. a producer reported feral swine
damage to a crop but no acres damaged or a producer reported on

Fig. 3. Non-fencing feral swine control questions from survey instrument.

Fig. 4. Fencing feral swine control questions from survey instrument.

electric and non-electric) were formatted differently because of the
fixed-cost nature of control via fencing.
The sample of producers was based on the MPPS sampling
design (Bailey and Kott, 1997) and NASS’s list of known operations
in the 11 states with the selected crops. 9720 surveys were mailed
during summer of 2015 and, upon non-response, followed by up to
10 phone calls for an interview. NASS does not allow disclosure of
any statistic if the maximum value of all values used to calculate the
statistic divided by the sum of those same values is greater than
0.42 or if fewer than four producers who answer the question
answered the question the same way. For this reason, summary
statistics at the state-crop level cannot be reported in some cases,
since the low response rate results in some categories being
dominated by a single producer. Thus, when zeroes are reported,
they should be interpreted as such. Alternatively, reported NA’s
could be zeroes or non-zeroes, but NASS would not allow the data
to be disclosed.
2. Results
A total of 9720 surveys were mailed and 4377 producers
responded to the survey (45% response rate). Table 1 presents a
summary of responses by state, including percentages of producers

crops other than those listed in Table 2). Table 2 reports the number
of usable observations for calculating percentage yield loss at the
state-crop level. Corn and soybeans provide the largest sample
sizes, although we also had reasonable numbers of responses for
wheat in some states. Given the pronounced regional nature of
their production, sample sizes for the remaining crops were unsurprisingly small or non-existent in some states.
The results of the yield loss calculations for the crops of interest
are presented in Table 3. Mean reported damage to corn was
markedly higher in Georgia (4.73%) and Florida (4.41%) than in
other states (next highest is Texas with 1.65% damage), while reported soybean damage was substantially higher in Florida (3.43%)
than in other states (next highest is South Carolina with 1.52%).
Reported wheat damage was most severe in Georgia (4.39%) and
Texas (3.05%), and rice damage was most severe in Texas (2.46%)
and Louisiana (1.26%). Of all the state and crop combinations, the
highest mean reported damage occurred in peanut production in
Texas (9.28%) and Alabama (6.17%). In fact, peanuts appear to incur
the most damage among the reported crops, followed by corn. Most
of these findings are expected given what we know about feral
swine behavior, distribution and the geographic distribution of the
production of these crops.
Estimates of production value lost to feral swine, as calculated in

A. Anderson et al. / Crop Protection 89 (2016) 89e94

focused hunting and trapping. Aerial hunting was rarely reported
outside of Texas, likely because of its high cost (Campbell et al.,
2010). Neither type of fencing (electric and non-electric) was
commonly used, although the use of non-electric fencing was more
common than electric. Given the crops that we focused on, this was
not a surprising result. Spending on each method of control during
2014 is reported in Table 6. Responding growers spent the most on
shooting on sight, followed by trapping. We choose not to extrapolate control spending to the state level because we lack data on
control methods in the context of specific crops, and it is thus unclear how to extrapolate correctly. However, we instead calculate
the average spending per producer represented by the sample
(Table 7).

Table 4
Approximate value of production lost to feral swine state-wide (1000 US $).

AL
AR
CA
FL
GA
LA
MS
MO
NC
SC
TX
sum

Corn

Soybeans

Wheat

Rice

Sorghum

Peanuts

Sum

$1949
$9284
NA
$1592
$22
$5295
$12,364
$0
$2737
$4583
$23,884
$61,710

$3080
$5305
NA
$388
$1273
$5682
$5110
$459
$787
$2815
$464
$25,363

$453
$1265
NA
NA
$3855
NA
$881
$27
$430
$1349
$20,232
$28,491

NA
$3721
$0
NA
NA
$4693
$163
$0
NA
NA
$4300
$12,877

NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
$20,775
$20,775

$15,841
NA
NA
$4006
NA
NA
NA
NA
$730
NA
$20,162
$40,739

$21,322
$19,575
$0
$5985
$5150
$15,670
$18,518
$486
$4684
$8747
$89,817
$189,955

93

3. Conclusion
(5) are presented in Table 4. For the selected crops and states which
are reportable, an estimated $190 million in crop production was
lost to feral swine damage in 2014. Note that this does not capture
the full impact of feral swine to producers of these crops in these
states. Feral swine damage to livestock and property, as well as
costs incurred from control measures aimed at preventing additional damage, all contribute to the overall cost of feral swine,
which, given the proportions reported in Table 1, are likely substantial. A comparison across crops shows that corn has the highest
value of reported crop losses ($61,710), followed by peanuts
($40,739). However, given the total value of production in the 11
states of the different crops, peanut production suffers much larger
monetary losses as a percentage of total production value. The results also indicate that Texas suffers substantially larger monetary
losses than other states ($89,817; the next highest loss occurs in
Alabama with $21,322), despite the fact that percentage losses are
not typically more severe than states in the Southeast.
The percentage of responding producers reporting use of each
control method are reported in Table 5. Shooting feral swine on
sight was the most common method, followed about equally by

Our findings suggest that of the states included in this study,
feral swine impose the largest burden on agricultural producers in
the Southeast and Texas. Reported damage was generally lower in
the California, Arkansas, and Missouri. However, in the case of
California, this result may be affected by the diversity of agricultural
production in the state. Fruit and vegetable production is common
throughout many parts of California, and it is possible that by targeting grain and soybean producers, we were simply not sampling
the relevant producers in California. In the case of Arkansas and
Missouri, the relatively low damage is (at least in part) explained by
Fig. 1. In much of Arkansas and all of Missouri, feral swine are a
relatively recent phenomenon. Thus, it may be the case that densities are lower than in the Southeastern states, or producers may
simply be less aware of the damage because it has not occurred
historically.
Furthermore, responses suggest that corn and peanuts suffer
more damage than the other crops we focused on. This finding
could have several causes. First, these crops may be inherently
more attractive or vulnerable to damage than the other crops, or

Table 5
Percentage of responses reporting use of control methods.

AL
AR
CA
FL
GA
LA
MS
MO
NC
SC
TX

Shoot on sight

Hunt w/dogs

Hunt w/out dogs

Aerial

Trap

Repellants

Electric fence

Non-electric fence

29%
18%
4%
39%
47%
36%
24%
1%
7%
24%
43%

13%
8%
NA
21%
30%
22%
14%
NA
3%
19%
15%

18%
13%
3%
27%
32%
19%
16%
NA
2%
13%
27%

1%
NA
NA
NA
NA
NA
NA
NA
NA
NA
17%

21%
13%
1%
31%
29%
25%
14%
0%
2%
15%
29%

1%
1%
NA
2%
2%
NA
NA
NA
1%
NA
1%

2%
1%
1%
2%
2%
NA
NA
NA
1%
2%
2%

6%
NA
1%
8%
7%
3%
NA
1%
1%
6%
8%

Table 6
Total cost of feral swine control by method.

AL
AR
CA
FL
GA
LA
MS
MO
NC
SC
TX

Shoot on sight

Hunt w/dogs

Hunt w/out dogs

Aerial

Trap

Repellants

Electric fence

Non-electric fence

$117,742
NA
NA
$19,901
$347,066
NA
$43,983
NA
NA
$55,905
$461,372

$52,200
NA
$0
NA
$139,100
$7150
NA
$0
NA
$21,700
$94,103

$47,780
$5630
NA
$9775
$166,956
NA
$15,900
$0
NA
NA
$253,873

NA
$0
$0
$0
$0
NA
$0
$0
$0
$0
$344,000

$129,095
$29,350
$0
$35,550
$130,300
$22,210
$30,200
$0
NA
$60,004
$254,401

NA
NA
NA
NA
NA
NA
NA
$0
NA
NA
$3400

$8150
NA
NA
NA
NA
$0
NA
$0
NA
NA
NA

NA
NA
NA
$7395
$11,908
NA
NA
NA
NA
$8048
$59,845

94

A. Anderson et al. / Crop Protection 89 (2016) 89e94

Table 7
Average spending on feral swine control by method.

AL
AR
CA
FL
GA
LA
MS
MO
NC
SC
TX

Shoot on sight

Hunt w/dogs

Hunt w/out dogs

Aerial

Trap

Repellants

Electric fence

Non-electric fence

$349.38
NA
NA
$125.16
$899.13
NA
$239.04
NA
NA
$149.88
$483.62

$154.90
NA
$0.00
NA
$360.36
$55.43
NA
$0.00
NA
$58.18
$98.64

$141.78
$27.87
NA
$61.48
$432.53
NA
$86.41
$0.00
NA
NA
$266.11

NA
$0.00
$0.00
$0.00
$0.00
NA
$0.00
$0.00
$0.00
$0.00
$360.59

$383.07
$145.30
$0.00
$223.58
$337.56
$172.17
$164.13
$0.00
NA
$160.87
$266.67

NA
NA
NA
NA
NA
NA
NA
$0.00
NA
NA
$3.56

$24.18
NA
NA
NA
NA
$0.00
NA
$0.00
NA
NA
NA

NA
NA
NA
$46.51
$30.85
NA
NA
NA
NA
$21.58
$62.73

they may be relatively more common in areas with high swine
densities. Alternatively (or additionally), producers of these crop
may be more willing to incur damage or less able to invest in
control effort. Admittedly, a final reason may be that damage is
simply more observable in certain crops. This is perhaps a believable explanation for corn in particular, since trampled areas would
be more apparent than for other crops. Nevertheless, responses
suggest that feral swine damage to crops is widespread. A total
production loss of nearly $190 million represents a substantial loss
for crop producers, many of which typically operate on very small
profit margins.
The economic burden of crop damage from feral swine is not
limited to the lost production; it also includes the substantial cost of
control efforts. Many growers reported applying a suite of control
methods, with shooting and trapping representing the largest
fraction of control costs. Taken together, the crop losses and control
costs are a substantial additional production cost for producers
within the current distribution of feral swine. Although such effects
are unaccounted for here, a small but real shift in production has
probably occurred as the range and density of feral swine has
increased. It has been shown that any change in relative production
costs of agricultural commodities will alter the distribution of
production. Thus, feral swine damage has probably lead to both a
decrease in production of vulnerable crops where they are present
and an (not-necessarily equal) increase elsewhere. The impacts are
also not limited to producers. Ultimately, some portion of any increase in production will be passed to consumers in the form of
higher prices.
Several limitations of the survey and its analysis should be
acknowledged. First, producers may not have accurate perceptions
of damage, and their estimates of control costs could be biased.
Such biases may be intentional or unintentional. Additionally, we
are unable to fully characterize all non-response bias that may be
present. NASS expended considerable effort to minimize the
number of non-responses, and the response rate was about 45%
which is quite good. However, the possibility of bias remains
because responders may have been more likely to incur damage
than non-respondents. Finally, sample sizes for some questions and
state-crop combinations is quite small, and in some cases NASS
rules prevent disclosure of any information garnered from specific
questions.
Our hope is that the results we present here will serve several

purposes. First, an understanding of which areas and crops experience the most damage will make any management more efficient.
Producers and government agencies expend considerable time and
effort managing feral swine damage, and knowing where the
problem is most severe will help these entities allocate their resources more appropriately. Second, USDA/APHIS Wildlife Services
has recently initiated a widespread feral swine control campaign. In
addition to guiding the implementation of this program, the findings we present can serve as a benchmark for evaluating this
control program. Thus, our hope is that this survey can be repeated
at regular intervals to ensure that the objectives of the control
program are being met and progress is being made against the
threat that feral swine represent to US agricultural producers.

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