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[DO NOT PUBLISH]
IN THE UNITED STATES COURT OF APPEALS
FOR THE ELEVENTH CIRCUIT
________________________
No. 15-14818
Non-Argument Calendar
________________________
D.C. Docket No. 5:14-cv-00241-MW-GRJ
SPRING CREEK FARMING COMPANY,
Plaintiff-Appellant,
versus
FEDERAL CROP INSURANCE CORPORATION,
RISK MANAGEMENT AGENCY OF THE UNITED STATES DEPARTMENT
OF AGRICULTURE,
U.S. DEPARTMENT OF AGRICULTURE,
SECRETARY, U.S. DEPARTMENT OF AGRICULTURE,
Defendants-Appellees.
________________________
Appeal from the United States District Court
for the Northern District of Florida
________________________
(June 29, 2016)
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Before WILSON, MARTIN and ROSENBAUM, Circuit Judges.
PER CURIAM:
This case requires us to decide whether a government agency acted
arbitrarily and capriciously by rejecting a peanut farmer’s crop insurance claim that
the crops did not get enough rain. Because neither party had exact measures of
how much rainfall the crops received, the agency weighed the available evidence.
On the one hand, there was inexact weather data from several sources, which could
be used to approximate rainfall. On the other hand, there was evidence that the
crops got less rainfall than the data indicated, though much of that evidence came
from interested parties. The agency judged the objective data to be more
convincing. It also relied on a peanut farming expert’s opinion, which was based
on that data. On this record and giving due deference to the agency, we cannot say
that these decisions were arbitrary and capricious.
I.
The Federal Crop Insurance Corporation administers the federal crop
insurance program through an operating entity called the Risk Management
Agency (“RMA”),. See 7 C.F.R. § 400.701. Under this program, private insurers
indemnify farmers’ covered crop losses, and the Crop Insurance Corporation
reinsures those policies. If a farmer claims a loss greater than $500,000, the
private insurer must notify the RMA, and the RMA can choose to intervene in the
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claim (as it did in this case). Also, a loss need not constitute an entire crop—
farmers can insure against low production yields caused by certain covered events.
See 7 C.F.R. § 457.8. In this case, the disputed event is “[a]dverse weather
conditions,” or more specifically, an alleged drought.
In 2012, Spring Creek Farming Company (“Spring Creek”) planted 1,354
acres of peanuts on five farms in Jackson County, Florida. Spring Creek insured
its peanut crop through a Crop Insurance Corporation-approved private insurer,
and the policy included a yield guarantee. The parties do not dispute that Spring
Creek’s peanut harvest was less than the yield guarantee. Rather, they debate the
reason why it was. Spring Creek claims that regional drought caused the low
yield. The defendants argue that the peanuts received adequate rainfall to produce
a normal yield, so Spring Creek’s low yield was not a covered loss.
After intervening in the claim, the RMA’s regional office investigated and
denied it. Because Spring Creek did not record rainfall on its farms, the regional
office used other information to investigate the claim. First, the regional office
compiled weather data from a Florida Automated Weather Network station
(“weather station”) that is located approximately 17 miles away from Spring
Creek’s affected farms and measures actual rainfall. Second, the regional office
accessed weather data from the Center for Agribusiness Excellence (“the Center”)
that approximated rainfall for areas between weather stations based on “real time
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radar and real time weather information from the weather stations.” The Center
data were presented in half-mile grids, so Dr. Kathryn Taylor, an RMA employee,
averaged the data across grids if a farm covered more than one. Finally, the
weather station as well as the Center data were submitted to Dr. John Beasley, a
recognized peanut farming expert and agronomist. Based on his analysis of the
data, Dr. Beasley concluded, “I do not see lack of water as a reason for yield loss.”
The regional office denied Spring Creek’s claim “because drought was not the
cause of loss.”
Spring Creek requested that the RMA review the regional office’s decision.
The RMA first outlined each party’s position and evidence. Then, it cross-
referenced the weather station and Center data with new weather data from a
system called PRISM, which showed similar quantities of rainfall in the area of
Spring Creek’s farms. The RMA upheld the regional office’s finding that drought
was not the cause of the loss.
Next, Spring Creek appealed to the United States Department of
Agriculture’s (“USDA”) National Appeals Division (“NAD”), which offers two
rounds of administrative review. In the first round, Spring Creek presented its
evidence to an NAD hearing officer at an evidentiary hearing that lasted several
days. The NAD hearing officer affirmed the agency decision, stating that the
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RMA had relied on credible evidence. In the second round, the NAD director also
upheld the decision.
Spring Creek then sought judicial review of the final agency decision in the
district court. It argued that the RMA’s decision was arbitrary, capricious, and not
supported by substantial evidence. The district court granted summary judgment
for the defendants. The court concluded that the agency’s decision to favor some
evidence over other evidence was not arbitrary and capricious. Spring Creek
timely appealed to this Court.
II.
This Court reviews de novo a district court’s grant of summary judgment,
applying the same standard as the district court. Mahon v. U.S. Dep’t of Agric.,
485 F.3d 1247, 1252 (11th Cir. 2007). Under the Administrative Procedures Act, 5
U.S.C. § 701 et seq., federal courts shall set aside agency decisions that are
“arbitrary, capricious, an abuse of discretion, or otherwise not in accordance with
law.” Id. § 706(2)(A). “To make this finding the court must consider whether the
decision was based on a consideration of the relevant factors and whether there has
been a clear error in judgment.” Citizens to Preserve Overton Park, Inc. v. Volpe,
401 U.S. 402, 416, 91 S. Ct. 814, 823–24 (1971), abrogated on other grounds,
Califano v. Sanders, 430 U.S. 99, 97 S. Ct. 980 (1977). This is a deferential
standard, and “we cannot substitute our own judgment for that of the agency.”
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Alabama-Tombigbee Rivers Coalition v. Kempthorne, 477 F.3d 1250, 1254 (11th
Cir. 2007).
A court must also consider whether the agency decision was not supported
by “substantial evidence” in the record. 5 U.S.C. § 706(2)(E). The substantial
evidence test is similar to the arbitrary and capricious standard, but it applies to
factual findings. See Fields v. Dep’t of Labor Admin. Review Bd., 173 F.3d 811,
813 (11th Cir. 1999) (per curiam). Substantial evidence is “such relevant evidence
as a reasonable mind might accept as adequate to support a conclusion.” Stone &
Webster Constr., Inc. v. U.S. Dep’t of Labor, 684 F.3d 1127, 1133 (11th Cir. 2012)
(quotation omitted). “The substantial evidence standard limits the reviewing court
from deciding the facts anew, making credibility determinations, or re-weighing
the evidence.” Id. (quotation omitted). The fact that the record may support a
contrary conclusion is not enough. DeKalb Cty. v. U.S. Dep’t of Labor, 812 F.3d
1015, 1020 (11th Cir. 2016).
III.
It is undisputed that no actual rainfall collection data was available for
Spring Creek’s farms, because Spring Creek did not record it and the nearest
weather station is approximately 17 miles away. The agency was therefore forced
to work with imperfect data, as is often the case. Spring Creek says the agency
should’ve weighed the evidence in its favor, alleging a number of flaws with the
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evidence as well as the agency’s decisionmaking process. Spring Creek makes two
broad challenges: to the measurement of rainfall, and to the assessment of the
peanuts’ water requirements relative to that rainfall. Neither challenge warrants
overturning the agency’s decision.
A. Rainfall Measurements
Spring Creek claims the agency’s rainfall measurements were inaccurate for
three reasons. First, the data were unreliable because they were based on
“manipulated” estimates and an unknown methodology. Second, the evidence
presented by Spring Creek was more compelling. Finally, other farmers’ drought
claims were paid within the same geographical area.
1. Data reliability.
Spring Creek alleges that the agency improperly used unreliable rainfall
estimates. It claims the data were unreliable because they merely estimated rainfall
on Spring Creek’s farms; because the RMA had to average the Center data for
some farms; and because the methodology for obtaining that data is unknown.
First, Spring Creek is correct that the data were based on estimates, but estimates
were the only measurements available. In the absence of exact measurements, the
agency did not act arbitrarily and capriciously by considering weather data that
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approximated rainfall for areas between weather stations.1 These data were clearly
a “relevant factor.” See Overton Park, 401 U.S. at 416, 91 S. Ct. at 823–24.
Spring Creek also argues that the RMA “unscientifically manipulated” the
Center data by running them through “formulas.” This point is overstated. The
record shows that, if a given peanut farm covered more than one half-mile grid, Dr.
Taylor calculated a “simple average” 2 of the Center data for those grids, which
would represent average rainfall for that farm. Spring Creek does not explain why
this process was scientifically unsound or how it adversely impacted the quality of
the Center data—instead, Spring Creek’s argument seems to be that any secondary
treatment of the data was inherently unreliable. Yet Spring Creek does not propose
a superior method for blending the Center data between half-mile grids. 3 We
cannot say it was a “clear error in judgment” for the agency to consider these data.
Id.
Spring Creek’s last challenge to the data is based on the methodology used
to generate them, which Spring Creek claims is not in the record. Spring Creek
quotes parts of Dr. Taylor’s testimony to support this argument. However, a full
review of Dr. Taylor’s testimony shows that she repeatedly stated the Center data
1
The agency also considered actual rainfall collection data for the nearest weather
station. However, that station was 17 miles away and may have experienced different rainfall.
(1+2+3)
2
As an example, 3 = 2 is the simple average of 1, 2, and 3.
3
Spring Creek also rejects the use of a weighted average, which Dr. Taylor later used to
check the accuracy of her original calculations.
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were generated by means of radar reflectance, which creates a signal when
outgoing radar waves are reflected back after encountering precipitation in the
atmosphere. In fact, Dr. Taylor testified she was “certain” that the Center data
were obtained “us[ing] radar data and . . . real time data, from weather stations.”
Dr. Taylor clarified that she was only uncertain about how similar the computer
models for the Center and PRISM were, and that they might be slightly different,
although their data output “by and large agree[s].” 4 Thus, contrary to Spring
Creek’s assertion, the methodology used to generate the Center data was not
unknown. The agency did not act arbitrarily and capriciously by considering these
data.
2. Competing evidence.
4
The uncertainty about modeling does not seem to have been clarified elsewhere. Spring
Creek argues this is because the USDA arbitrarily and capriciously denied its request to
subpoena an employee of the Center to testify on the subject. A subpoena may issue in an NAD
hearing only if: (1) the person being subpoenaed “possesses information that is pertinent and
necessary” to the proceeding; (2) “the information cannot be obtained except through testimony
of the person”; and (3) “the testimony cannot be obtained absent issuance of a subpoena.” 7
C.F.R. § 11.8(a)(2)(iii)(B). The NAD hearing officer ultimately denied Spring Creek’s subpoena
request because the desired testimony was “in the nature of expert testimony, and the Agency
Record does not reveal that [the RMA] consulted with a person within [the Center] to interpret
any data obtained from [it]. . . . The relevant information Appellant seeks can be obtained by
examining [the RMA]’s representative(s) . . . and/or by retaining its own expert.” In other
words, because RMA personnel used the Center’s resources but did not rely on its employees,
the desired information could be obtained without the requested testimony. See id. Even
assuming (without deciding) that RMA representatives could not or would not supply the desired
information, as Spring Creek briefly alleges, Spring Creek does not allege that it was unable to
hire an expert to testify regarding the Center’s modeling. The hearing officer’s subpoena denial
was not arbitrary and capricious.
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Next, Spring Creek claims the agency improperly weighed the evidence.
Spring Creek points to competing evidence it introduced, including witness
testimony (much of it from Spring Creek insiders), photographic exhibits of crops,
and several weather or agricultural reports. But courts cannot re-weigh the
evidence on agency review. See Stone & Webster Constr., 684 F.3d at 1133. The
agency considered and discounted Spring Creek’s competing evidence, and we
cannot simply substitute our own judgment. See Alabama-Tombigbee Rivers
Coalition, 477 F.3d at 1254. Spring Creek’s evidence was discounted by the
agency because much of it was ambiguous or unsupportive. For instance, affiliates
of Spring Creek vaguely testified they did not recall “significant,” “meaningful,” or
“big” rains during parts of the growing season, but they had no rainfall records and
could not remember whether there were lighter rains. And a crop consultant who
viewed peanut plants on Spring Creek’s farms from across the road said the crop
“looked like a good stand,” and nothing about the crop “stood out to [him].”
Although Spring Creek presented some other evidence of a drought, it is not
enough that the evidence could support a decision contrary to that made by the
agency. See DeKalb Cty., 812 F.3d at 1020. On this record, we cannot say the
agency improperly weighed the evidence.
3. Other insurance claims.
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Spring Creek’s final challenge to the rainfall measurements arises from the
payment of several crop insurance claims filed by other farmers in Jackson County,
Florida. The fact that these farmers were located nearby and recovered on drought
claims, Spring Creek argues, is evidence of a regional drought. Thus, Spring
Creek concludes that the agency acted arbitrarily and capriciously under this
Court’s precedent in Mahon. Spring Creek’s reliance on Mahon is misplaced. In
Mahon, some nurseries in Florida with expired licenses suffered losses from a
freeze and applied for disaster assistance. Id. at 1249. The USDA denied relief to
the plaintiff nurseries because their licenses were expired, but the evidence showed
that the USDA granted relief to other nurseries with expired licenses. Id. at 1249–
51. Because all the nurseries had expired licenses, this Court held that the
nurseries were “similarly situated,” and the USDA acted arbitrarily and
capriciously “by treating similarly situated producers differently.” Id. at 1260.
Unlike in Mahon, it is not so easy to declare Spring Creek and the other
claimants “similarly situated.” While determining the expiration date of a license
is relatively simple, deciding whether (and to what extent) a farmer’s crop yield
has been affected by drought is rather more difficult, as this case demonstrates.
Indeed, Spring Creek put forward evidence suggesting that rainfall may be variable
not just within Jackson County, but even within a single field. Spring Creek did
not present evidence that the other farmers’ fields received a similar quantity of
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rainfall or that the fields were planted at the same time. For these reasons, Mahon
does not apply.
B. Crop Requirements
Spring Creek also challenges the agency’s determination of crop
requirements, and whether those requirements were satisfied. Dr. Beasley, a
recognized peanut farming expert, concluded that the rainfall data discussed above
were sufficient for a peanut crop in Jackson County, Florida, to avoid yield loss,
and the agency relied on his opinion. Spring Creek argues this conclusion was
flawed for three reasons: (1) it failed to consider all the variables; (2) it
misinterpreted the data; and (3) it was based on a faulty assumption.
1. Variables.
First, Spring Creek claims that the RMA’s conclusion ignored important
variables such as soil temperature and type. But it is not clear that Dr. Beasley’s
analysis, on which the RMA relied, ignored these variables. When the RMA sent
the rainfall data to Dr. Beasley for analysis, it asked him if the rainfall “would have
caused a significant [peanut] yield loss given the regular recharge of the soil
moisture” that took place “in this particular Florida County.” (Doc. 23-4: 54
(emphasis added)). This focus on the moisture level in the soil—which would
implicate variables other than rainfall, such as soil temperature and type—belies
Spring Creek’s claim that Dr. Beasley merely analyzed crops grown “in a
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vacuum.” Instead, his analysis apparently considered soil moisture requirements
for peanuts grown in a specific place during a specific time period. Unless Dr.
Beasley failed to consider the RMA’s question and data—and Spring Creek
presents no evidence that occurred—Dr. Beasley necessarily made certain
assumptions about the conditions for peanut farming in Jackson County, Florida,
during the relevant time period. The RMA did not make a clear error of judgment
by relying on Dr. Beasley’s expertise.
2. Data interpretation.
Second, Spring Creek argues that the RMA arbitrarily relied on Dr.
Beasley’s analysis because he misinterpreted the rainfall data. Even accepting the
rainfall data, Spring Creek argues, Dr. Beasley’s conclusion is anomalous because
the peanut farms received less than the target amount of rainfall in many key
growing weeks. It’s true that the farms received less than the target amount of
rainfall in some weeks—a fact that is expressly incorporated into the RMA’s
question to Dr. Beasley. In other weeks, though, the farms received much more
than the target amount of rainfall: during the week of August 4 to August 8, in
particular, the data showed heavy rainfall across all of Spring Creek’s peanut
farms. Dr. Beasley is a peanut farming expert. As a court, we cannot determine
whether heavy rainfall in one week can compensate for lesser rainfall in another
week, nor can we say how minimal rainfall must be before it significantly reduces
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crop yields. Dr. Beasley made those determinations and arrived at an opinion. The
agency did not act arbitrarily by relying on it.
3. Faulty assumption.
Lastly, Spring Creek argues that Dr. Beasley’s opinion cannot be substantial
evidence because he relied on a faulty assumption: that all of Spring Creek’s
peanut farms were planted on May 5, 2012. In fact, only one of Spring Creek’s
peanut farms was planted on May 5, and the rest were planted between May 19 and
May 23. This detail does not seem to have been accounted for in the data given to
Dr. Beasley. However, Spring Creek fails to explain how this “faulty assumption”
renders the entire agency decision arbitrary and capricious, or how it transforms
Dr. Beasley’s opinion into insubstantial evidence. Other than pointing this
oversight out, Spring Creek has not explained what adverse effect it would have.5
The RMA’s clerical error is not enough to carry the day for Spring Creek.
* * *
Because Spring Creek has not satisfied the heavy burden of showing that the
agency’s actions were arbitrary, capricious, or not supported by substantial
evidence, we must AFFIRM.
AFFIRMED.
5
When the omission is added back into the mix, total estimated rainfall in the affected
fields during the key growing weeks actually increases by between 0.84 and 2.36 inches,
depending on the farm. In other words, had Dr. Beasley received the correct planting dates, he
would have seen more total rainfall during the key growing weeks, not less.
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