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Navelski v. International Paper Co.

United States District Court, N.D. Florida, Pensacola Division

March 25, 2017

JOHN NAVELSKI, et al., Plaintiffs,
v.
INTERNATIONAL PAPER COMPANY, Defendant.

          ORDER

          M. CASEY RODGERS CHIEF UNITED STATES DISTRICT JUDGE.

         This matter is before the Court on five motions: (1) Plaintiffs' Motion for Class Certification, ECF No. 61; (2) Defendant's Motion to Exclude Expert Testimony from Tom Fruitticher, MAI, ECF No. 77; (3) Defendant's Motion to Exclude Expert Testimony from Mark Ross, Ph.D., P.E., ECF No. 78; (4) Plaintiffs' Motion to Limit or Exclude Expert Testimony of Richard J. Roddewig, ECF No. 80; and (5) Defendant's Motion for Summary Judgment, ECF No. 81. The Court's rulings are set forth below.

         I. Background

         A heavy, slow-moving rainstorm entered Escambia County, Florida on the afternoon of April 29, 2014, where it remained through the early hours of April 30, 2014. The events that led to this litigation occurred during the course of this extraordinary storm, when the Elevenmile Creek overflowed its banks and approximately 160 homes in the Bristol Park, Bristol Woods, Bristol Creek, and Ashbury Hills subdivisions of Cantonment, Florida were flooded. The Elevenmile Creek is a 13-mile stream located within the Elevenmile Creek watershed in Escambia County. The watershed has a 47.97-square-mile drainage area that reaches from Cantonment to Perdido Bay, Florida. Defendant International Paper Company, a New York corporation, owns and operates a paper mill in Cantonment. The Elevenmile Creek runs through Defendant's property. Prior to 2012, the paper mill's wastewater was filtered through various holding ponds on Defendant's property and then discharged into the Elevenmile Creek through the Kingsfield Road Dam, which was also located on Defendant's property.[1] In 2012, Defendant stopped using the Dam to discharge wastewater and, instead, began moving it by pipeline to the wetlands above Perdido Bay. The Dam, however, remained in place and continued to impound storm water runoff from Defendant's property. It is undisputed that, during the subject storm, the Dam collapsed, discharging the stormwater impounded behind it into the Elevenmile Creek.

         Plaintiffs are current and former property owners in the Bristol Park, Bristol Woods, Bristol Creek, and Ashbury Hills subdivisions. Their properties are situated along the Elevenmile Creek, approximately two miles downstream from Defendant's paper mill and the Dam.[2] Plaintiffs allege that the flooding they experienced was caused or made more severe by the collapse of the Dam, which they claim resulted from Defendant's failure to properly maintain or remove it.

         Plaintiffs filed this action against Defendant in the Circuit Court of Escambia County, Florida on May 13, 2014. ECF No. 1-1. On September 2, 2014, Defendants removed the action to this Court under the Class Action Fairness Act and diversity jurisdiction. See ECF No. 1. In their First Amended Complaint, Plaintiffs assert claims for negligence, trespass, nuisance, and strict liability. ECF No. 38. Plaintiffs now move for class certification, ECF No. 61, which Defendant opposes, ECF No. 65. Both the motion and the response in opposition are supported by expert testimony. Each side challenges the other's experts as unreliable and those motions are also pending. ECF Nos. 77, 78, 80. Finally, Defendant has moved for summary judgment. ECF No. 81. The Court held a three-day evidentiary hearing on all motions.[3] Now, having fully considered the law, the voluminous record, and the arguments of the parties, the Court rules as follows.

         II. Expert Challenges

         In support of their motion for class certification, Plaintiffs have proffered Dr. Mark A. Ross as an expert on the cause of the flooding in the subject neighborhoods. Plaintiffs have also proffered Tom Fruitticher as an expert on damages. Defendant has proffered Richard J. Roddewig as an expert to rebut Fruitticher's opinions. Each side now moves to exclude the other's expert testimony under Federal Rule of Evidence 702 and Daubert v. Merrell Dow Pharm., Inc., 509 U.S. 579 (1993). Because this expert testimony is challenged as unreliable and is also critical to class certification, the Court must perform a full Daubert analysis before resolving the class certification motion.[4] See Sher v. Raytheon Co., 419 Fed App'x 887, 890 (11th Cir. 2011) (quoting Am. Honda Motor Co. v. Allen, 600 F.3d 813, 815-16 (7th Cir. 2010) (per curiam)). For the reasons that follow, the Court finds that the expert testimony of both Dr. Ross and Roddewig is admissible; however, Fruitticher's testimony must be excluded.

         A. Legal Standard

         Rule 702, [5] as explained by Daubert and its progeny, governs the admissibility of expert testimony. Rink v. Cheminova, Inc., 400 F.3d 1286, 1291 (11th Cir. 2005). Under Rule 702 and Daubert, district courts are compelled to act as “gatekeepers” to ensure the reliability and relevancy of expert testimony. Id. (quoting Daubert, 509 U.S. at 589). Expert testimony is reliable and relevant-and, therefore, admissible-when the following criteria are met: (1) the expert is sufficiently qualified to testify about the matters he intends to address; (2) the methodology used is “sufficiently reliable as determined by the sort of inquiry mandated in Daubert; and (3) the testimony assists the trier of fact, through the application of scientific, technical, or specialized expertise, to understand the evidence or to determine a fact in issue.” Id. The Eleventh Circuit refers to these criteria separately as “qualification, reliability, and helpfulness, ” United States v. Frazier, 387 F.3d 1244, 1260 (11th Cir. 2004), and has emphasized that they are “distinct concepts that courts and litigants must take care not to conflate, ” Quiet Tech. DC-8, Inc. v. Hurel-Dubois UK Ltd., 326 F.3d 1333, 1341 (11th Cir. 2003). The party offering the expert has the burden of showing, by a preponderance of the evidence, that each of these requirements is met. Rink, 400 F.3d at 1292.

         To meet the qualification requirement, a party must show that its expert has sufficient “knowledge, skill, experience, training, or education” to form a reliable opinion about an issue that is before the court. Hendrix ex rel. G.P. v. Evenflo Co., Inc., 609 F.3d 1183, 1193 (11th Cir. 2010) (citing Fed.R.Evid. 702) (“Hendrix II”). The qualifications standard for expert testimony is “not stringent” and “[s]o long as the witness is minimally qualified, objections to the level of [his] expertise [go] to credibility and weight, not admissibility.” Hendrix v. Evenflo Co., Inc., 255 F.R.D. 568, 585 (N.D. Fla. Jan. 28, 2009) (“Hendrix I”).

         To meet the reliability requirement, an expert's opinion must be based on scientifically valid principles, reasoning, and methodology that are properly applied to the facts at issue. Frazier, 387 F.3d at 1261-62. The reliability analysis is guided by several factors: (1) whether the scientific technique can be or has been tested; (2) whether the theory or technique has been subjected to peer review or publication; (3) whether the technique has a known or knowable rate of error; and (4) whether the technique is generally accepted in the relevant community. Daubert, 509 U.S. at 593-94. “[T]hese factors do not exhaust the universe of considerations that may bear on the reliability of a given expert opinion, and a federal court should consider any additional factors that may advance its Rule 702 analysis.” Quiet Tech., 326 F.3d at 1341. The court's focus must be on the expert's principles and methodology, not the conclusions they generate. Daubert, 509 U.S. at 595. The test for reliability is “flexible” and courts have “broad latitude” in determining both how and whether this requirement is met. Kumho Tire Co., Ltd. v. Carmichael, 526 U.S. 137, 141-42 (1999).

         Finally, to satisfy the helpfulness requirement, expert testimony must be relevant to an issue in the case and offer insights “beyond the understanding and experience of the average citizen.” United States v. Rouco, 765 F.2d 983, 995 (11th Cir. 1985). Relevant expert testimony “logically advances a material aspect of the proposing party's case” and “fits” the disputed facts. McDowell v. Brown, 392 F.3d 1283, 1298-99 (11th Cir. 2004). Expert testimony does not “fit” when there is “too great an analytical gap” between the facts and the proffered opinion. Gen. Elec. Co. v. Joiner, 522 U.S. 136, 147 (1997). When scrutinizing the reliability and relevance of expert testimony, a court must remain mindful of the delicate balance between its role as a gatekeeper and the jury's role as the ultimate factfinder. Frazier, 387 F.3d at 1272. The court's gatekeeping role “is not intended to supplant the adversary system or the role of the jury.” Allison v. McGhan Med. Corp., 184 F.3d 1300, 1312 (11th Cir. 1999). Only the jury may determine “where the truth in any case lies” and the court “may not usurp this function.” Frazier, 387 F.3d at 1272. Thus, a court may not “evaluate the credibility of opposing experts” or the persuasiveness of their conclusions, Quiet Tech, 326 F.3d at 1341; instead, its duty is limited to “ensur[ing] that the fact-finder weighs only sound and reliable evidence, ” Frazier, 387 F.3d at 1272.

         B. Dr. Mark A. Ross

         Plaintiffs have proffered the expert testimony of Mark A. Ross, Ph.D., P.E.[6](“Dr. Ross”), a civil engineer and professor at the University of South Florida with extensive experience in the areas of hydrologic and hydraulic modeling.[7] Dr. Ross has offered his opinion that the flooding of Plaintiffs' properties was caused or made more severe by the failure of the Kingsfield Road Dam. Defendant does not dispute Dr. Ross's qualifications to opine as an expert on flood causation. Nor does Defendant deny that expert testimony regarding the cause of the flooding in this case would assist the factfinder in determining Defendant's liability. Defendant's sole challenge is to the reliability of Dr. Ross's methodology. More specifically, Defendant argues that Dr. Ross's testimony should be excluded because he did not reliably apply a differential etiology in reaching his opinions.

         As an initial matter, Defendant characterizes Dr. Ross's methodology as a species of differential etiology, which is a well-recognized “scientific technique of identifying the cause of a medical problem by eliminating the likely causes until the most probable one is isolated.” Kilpatrick v. Breg, Inc., 613 F.3d 1329, 1336 n.7 (11th Cir. 2010) (quoting Westberry v. Gislaved Gummi AB, 178 F.3d 257, 262 (4th Cir. 1999)). The Eleventh Circuit has explained that “when applied under circumstances that ensure reliability, the differential etiology method can provide a valid basis for medical causation opinions.”[8] Hendrix II, 609 F.3d at 1195. The instant case, however, does not involve medical causation and the traditional evidentiary foundations that have proven reliable in that context are unsuitable for analyzing the causation question presented here.[9] This is, in part, because the reliability of medical causation opinions often turns on a challenge to the core science on which the opinions are based. See, e.g., Chapman v. Procter & Gamble Distributing, LLC, 766 F.3d 1296, 1308 (11th Cir. 2014) (affirming exclusion of expert testimony where no “recognized methodology” or evidence established generally that Fixodent is capable of causing myelopathy); Hendrix II, 609 F.3d 1183 (affirming exclusion of expert testimony where no scientifically reliable evidence supported conclusion that traumatic brain injury can cause autism).

         In this case, the core science is not in dispute, as Defendant concedes the general scientific proposition that a dam failure can cause a river or stream to overflow its banks and flood adjoining neighborhoods. Notably, Dr. Ross did not himself refer to his methodology as differential etiology or any variation of that technique. Moreover, as discussed in greater detail below, Dr. Ross's analysis relied primarily on data specific to the subject storm and watershed, whereas a traditional differential analysis ordinarily is based on more generalized scientific assumptions extrapolated from external sources. Thus, while the Court finds that Dr. Ross's approach bears some resemblance to differential etiology, it is “more aptly characterized as a process of reasoning to the best inference, ” in which logical inferences “are drawn about a particular proposition or event by a process of eliminating all other possible conclusions to arrive at the most likely one, the one that best explains the available data.”[10] See Bitler v. A.O. Smith Corp., 400 F.3d 1227, 1237 n.5 (10th Cir. 2005). Even so, because the two approaches share broadly analogous analytical frameworks, the Court will evaluate the reliability of Dr. Ross's causation testimony using the differential etiology construct adopted by the parties.

         An expert whose opinions are the product of differential etiology must show that the technique was reliably employed in the context of a particular case. See Hendrix II, 609 F.3d at 1195; see also, Kilpatrick, 613 F.3d at 1342. A reliable differential analysis is performed in two steps. Id. First, the expert identifies the scientifically possible explanations for the harm at issue. See id. The issue at this “ruling in” stage is general causation, which focuses on whether a mechanism or event is “generally capable of causing” the type of harm alleged by the plaintiff. See id.; see also McClain v. Metabolife Int'l, Inc., 401 F.3d 1233, 1239 (11th Cir. 2005). Second, the expert systematically and scientifically rules out each potential explanation “until reaching one that cannot be ruled out or determining which of those that cannot be excluded is the most likely.” Guinn v. AstraZeneca Pharmaceuticals LP, 602 F.3d 1245, 1253 (11th Cir. 2010). This second step focuses on specific causation, which requires a showing that the mechanism or event in question actually did cause the plaintiff's harm. Chapman, 766 F.3d at 1308. In this case, Defendant contends that Dr. Ross's methodology does not reliably establish either general or specific causation. The Court disagrees.

         1.General Causation

         With respect to general causation, the Court finds that Dr. Ross appropriately “ruled in” the failure of the Kingsfield Road Dam as a possible cause of the flooding in the subject neighborhoods. General causation is established by a demonstration, through a scientifically valid methodology, that a mechanism or event can cause a particular result. Hendrix II, 609 F.3d at 1196. The core science with respect to general causation in this case-that the failure of a dam can cause a river or stream to overflow its banks and flood adjoining neighborhoods-is well-established and uncontroverted.[11] This fact alone would suffice to establish general causation under Daubert. See McClain, 401 F.3d at 1239 (“The court need not undertake an extensive Daubert analysis on the general toxicity question when the medical community recognizes that the agent causes the type of harm a plaintiff alleges.”); see also Chapman, 766 F.3d at 1303 (“In cases where the cause and effect or resulting diagnosis has been proved and accepted by the medical community, federal judges need not undertake an extensive Daubert analysis on the general toxicity question.”); Bitler, 400 F.3d at 1235-37 (expert's theory that copper sulfide particles caused propane explosion sufficiently reliable where supported by physical evidence, fire investigator's professional experience, and undisputed “core science” of copper sulfide particulate contamination as a cause of propane gas leaks). But, it is noteworthy in this case that Dr. Ross based his causation opinion on considerably more evidence than just the universally accepted science of dam failures and water flow, as his methodology also accounts for the specific drainage characteristics of this dam and real-time rainfall data from this storm. More specifically, Dr. Ross testified that he examined the Dam site, the subject neighborhoods, and the topographic, hydrologic, and vegetation characteristics of the Elevenmile Creek watershed. Dr. Ross also analyzed historical rain gauge data collected by the United States Geological Survey (USGS) in conjunction with Next-Generation Radar (NEXRAD) precipitation data to calculate the spatial and temporal distribution of the rainfall over the Elevenmile Creek watershed during the Storm. Additionally, he calculated the dimensions of the Dam, its static storage and its dynamic storage, using a computer-based hydrologic model (Hydrological Simulation Program--Fortran, or HSPF) of the actual rainfall conditions during the Storm.[12]

         From this physical evidence and empirical data, Dr. Ross was able to conclude that the flooding in the subject neighborhoods could have been caused by either: (1) the amount and distribution of the rainfall during the Storm, alone; or (2) the amount and distribution of the rainfall, together with the failure of the Kingsfield Road Dam. Defendant has offered no evidence or even argument to question the core science underlying Dr. Ross's opinion or the reliability of his models. On the contrary, Defendant's expert, Dr. Frank Lan, confirmed that Dr. Ross used appropriate industry models to analyze the rainfall and water flow in this case, and he took no issue with the data on which the models were based. The Court, therefore, finds that Dr. Ross's reliance on the known science of dam failures and water flow, together with the data he gathered with respect to the unique characteristics of the subject watershed, dam, and rainfall event, constitutes a scientifically valid methodology for “ruling in” the failure of the Kingsfield Road Dam as a possible cause of the subject flooding. Dr. Ross's opinion is “properly grounded, well-reasoned, and not speculative.” See Frazier, 387 F.3d at 1296. Nothing in Rule 702 or Daubert requires more. The appropriate way to assess the validity and strength of Dr. Ross's conclusions is through “[v]igorous cross-examination, presentation of contrary evidence, and careful instruction on the burden of proof.” See Daubert, 509 U.S. at 596.

         Defendant insists that Dr. Ross's general causation opinion is unreliable because he did not “model or test his dam failure hypothesis” by designing an exact simulation of the process by which the Kingsfield Road Dam could have failed and flooded the subject neighborhoods. Taking this argument to its logical conclusion, Defendant would have Plaintiffs prove causation to a scientific certainty before expert testimony could be admitted. The Court finds this argument wholly inconsistent with Daubert and the fundamental premise of Rule 702. See Daubert, 509 U.S. at 590 (“Of course, it would be unreasonable to conclude that the subject of scientific testimony must be ‘known' to a certainty; arguably, there are no certainties in science.”). “[T]esting is not necessary in all instances to establish reliability under Daubert, ” particularly where an expert's conclusion is premised on well-established and undisputed scientific knowledge. Bitler, 400 F.3d at 1236. On this point, the Tenth Circuit's decision in Bitler v. A.O. Smith Corp., is instructive. In Bitler, the plaintiffs' experts opined that a propane explosion in a home was caused by copper-sulfide contamination of the safety valve seat of a water heater. Id. at 1231. The defendants challenged the admission of plaintiffs' experts' opinions for, among other reasons, failure to test their theory that copper sulfide had passed through a mesh screen before lodging on the safety valve seat. Id. at 1235. The Tenth Circuit observed that the experts' theory of the accident was based on the “known science of copper sulfide particulate contamination as a cause of propane gas leaks” and that testing of this established scientific principle would generally be unnecessary. Id. at 1236. The court reasoned that while the presence of a mesh screen designed to filter out those particles may have changed the jury's causation determination, it did not “fundamentally and necessarily change[] the nature of the underlying science.” Id. Thus, because the “core science-that copper sulfide particles are the kind of thing that when lodged on the valve seat can cause leaks- [was] sufficiently well-established, ” the court concluded that testing was not required to permit the plaintiffs' experts to opine on the cause of the explosion. Id. The same is true here.

         2. Specific Causation

         With respect to specific causation, Defendant argues that Dr. Ross did not reliably “rule out” alternative explanations for the flooding in the subject neighborhoods. In particular, Defendant claims that Dr. Ross failed to consider and eliminate the possibility that the flooding was caused or impacted by either: (1) the actual distribution of the rainfall during the Storm alone; or (2) the increased vegetation along the path of the flood. According to Defendant, Dr. Ross's analysis thus is not sufficiently reliable to support his opinion on specific causation. This is incorrect.

         Contrary to Defendant's assertion, the evidence shows that Dr. Ross did account for the distribution of the rainfall during the Storm, as that data drove the computer-based modeling programs he used to simulate the rainfall event. Dr. Ross testified that he collected data about the amount, duration, and varying intensities of the rainfall over the Elevenmile Creek watershed during the subject storm from both the USGS and the National Oceanic and Atmospheric Administration (NOAA).[13]Dr. Ross compared radar rainfall data with rain gauge measurements to estimate the spatial and temporal rainfall distribution over the Elevenmile Creek watershed during the Storm. He input these rainfall estimates into his hydrologic model, along with details about the physical characteristics of the Elevenmile Creek watershed, to compute the volume and timing of surface water runoff. These runoff calculations were combined with cross-sectional and frictional values from the Elevenmile Creek channel to produce a computerized hydraulic model (Hydraulic Engineering Center River Analysis System, or HEC-RAS) that could simulate the Storm's effect on the Elevenmile Creek watershed, in terms of the potential depths and duration of floodwaters, under two hypothetical scenarios-one approximating water flow conditions had the Kingsfield Road Dam remained intact and fully functioning during the Storm, and the other approximating the result had there been no dam in place and the Elevenmile Creek existed in a natural, unobstructed state. Under both hypothetical scenarios, the hydraulic model predicted a three to five-foot decrease in water depths during the Storm, which likely would have resulted in the flooding of no more than six houses in the subject neighborhoods. Because, together, the hydrologic and hydraulic models digitally approximated the actual rainfall conditions in the Elevenmile Creek watershed during the storm, these findings support Dr. Ross's conclusion that the rainfall alone could not have caused the flooding.

         The evidence also shows that Dr. Ross properly considered and ruled out the possibility that vegetation growing within the Elevenmile Creek channel caused or significantly contributed to the flooding of Plaintiffs' homes. According to both parties' experts, the density and distribution of vegetation along a river channel can impact the rate at which water flows through it. Dense vegetation and undergrowth, for example, can impede the flow of water, causing higher flood elevations. In hydraulic modeling, the collective effect of a channel's resistance to water flow is represented by a “roughness” parameter called a Manning's coefficient, also known as a frictional value. Dr. Ross testified that, to account for vegetation along the Elevenmile Creek main channel and flood plain, he selected frictional values of .03 and .05, respectively. Dr. Ross indicated that the procedure for estimating frictional values is relatively subjective, but that the figures he used were based on the vegetative characteristics he observed at the Elevenmile Creek and were “typical values for forested coastal-plain sub-tropical floodplains” like this one. See ECF No. 78-1 at 25. With the inclusion of these frictional values, Dr. Ross's hydraulic model accounted for the impact of vegetation on flood levels during the Storm. Dr. Ross did not test other, theoretical frictional values because he was satisfied that the values he selected accurately represented the roughness characteristics of Elevenmile Creek. That Defendant's expert disagrees and chose different, higher frictional values for use in his own hydraulic model does not render Dr. Ross's methodology unreliable. This objection goes to the weight of Dr. Ross's testimony, not its admissibility. The Court finds Dr. Ross's testimony admissible.

         C. Tom Fruitticher

         Plaintiffs seek classwide damages for the diminished values of their homes as a result of the alleged stigma that attaches to real property that has experienced flooding. In support of this claim, Plaintiffs have proffered the expert testimony of Tom Fruitticher, a state-certified general appraiser with over thirty years' experience appraising and valuating real property. Fruitticher has offered his opinion as to the expected percentage of reduction in the fair market value of Plaintiffs' properties as a result of the flooding. Defendant challenges Fruitticher's testimony on qualification, reliability, and helpfulness grounds.

         1. Qualification

         Fruitticher performed a series of statistical analyses, namely, multiple regression and linear regression analysis, to reach his conclusion as to stigma damages. Defendant contends that Fruitticher is not qualified to provide expert testimony based on multiple regression analysis because he is not a statistician, has not routinely employed this technique in valuing real properties, and lacks extensive training in its use and application in the mass appraisal context. In essence, Defendant argues that Fruitticher's general education and experience in the field of real property appraisal do not translate into qualifications that enable him to testify competently based on regression analysis in this case. Defendant reads the “qualification” prong of Rule 702 too stringently. “An expert is not necessarily unqualified simply because [his] experience does not precisely match the matter at hand.” Furmanite America, Inc. v. T.D. Williamson, Inc., 506 F.Supp.2d 1126, 1129 (M.D. Fla. 2007) (citing Maiz v. Virani, 253 F.3d 641, 665 (11th Cir. 2001)).[14] Again, “so long as the [expert] is minimally qualified, objections to the level of [his] expertise go to credibility and weight, not admissibility.” Hendrix I, 255 F.R.D. at 585. The critical question for qualification purposes is whether the proffered expert has such “knowledge, skill, experience, training, or education” that his opinion will aid the trier of fact in understanding the evidence or resolving a factual issue. See Fed. R. Evid. 702.

         In this case, the Court finds Fruitticher at least minimally qualified to use statistical analysis to assist the trier of fact in determining whether and to what extent Plaintiffs are entitled to so-called stigma damages. The record reflects that Fruitticher has spent thirty years appraising residential properties in the Pensacola area and, in that time, has performed “numerous” disaster-related diminished value assessments. This background equips him for the task of evaluating the impact of the subject flood on Plaintiffs' property values. Moreover, Fruitticher has formal training in the application of multiple regression analysis and has used the technique once before in connection with a mass appraisal valuation project. His experience with multiple regression analysis, though limited, is sufficient to support his proposed testimony in the area of statistics. A witness need not be the best or most qualified authority in a field to be admitted as an expert. See, e.g., Burgett v. Troy-Bilt LLC, 579 Fed. App'x 372, 378 (6th Cir. 2014) (“[I]t is an abuse of discretion to exclude testimony simply because the trial court does not deem the proposed expert to be the best qualified or because the proposed expert does not have the specialization that the court considers most appropriate.”) quoting Pineda v. Ford Motor Co., 520 F.3d 237, 244 (3d Cir. 2008); Robinson v. GEICO Ins. Co., 447 F.3d 1096, 1101 (8th Cir. 2006) (same); Bracey v. Jolley, No. 1:10-cv-4064-TCB, 2012 WL 12870257, at *3 (N.D.Ga. 2012) (“Rule 702 does not require a party to produce the ‘most qualified' expert.”). Fruitticher need only possess enough general knowledge of a subject that his testimony would likely assist the trier of fact. See, e.g., Maiz, 253 F.3d at 665 (economist was properly qualified to estimate damages resulting from real estate investment scheme even though he had no experience in real estate development); United States v. Hensel, 711 F.2d 1000, 1006 (11th Cir. 1983) (holding that trial court did not err in allowing witness with extensive background in arson investigation to testify as an expert on admiralty arson although most of his experience involved fires on land). Given Fruitticher's extensive experience in the appraisal industry, his knowledge of multiple regression analysis, and the liberal standard for admission of expert testimony under Rule 702, see Frazier, 387 F.3d at 1294, the Court concludes that he is qualified to offer his opinion as to stigma damages in this case. Objections to the level of his expertise go to the credibility and weight of his opinion, not its admissibility. See Hendrix I, 255 F.R.D. at 585.

         2. Reliability

         Defendant challenges the reliability of Fruitticher's methodology on multiple grounds.[15] First, Defendant argues that Fruitticher's methodology constitutes an improper combination of two different methodologies, rather than the proper application of a single methodology. Second, Defendant objects to Fruitticher's multiple regression analysis as an “impermissible black box opinion.” Third, Defendant objects to the reliability of Fruitticher's linear regression model and the data that he used to support his trend line analysis.

         a. Fruitticher's Methodology

         Fruitticher used a series of different techniques to evaluate the impact of the subject flooding on Plaintiffs' homes. First, he used multiple regression analysis to estimate the pre-flood market values of the homes in the subject neighborhoods. Next, he conducted two separate linear regression analyses of the actual sales prices of flooded and non-flooded homes within the subject neighborhoods during the one-year periods immediately before and after the subject flood.[16] Fruitticher's linear regression analyses revealed a downward trend in home values in the year following the flood. More specifically, under his linear regression model, the homes that flooded during the Storm exhibited a nine percent decline in value and the non-flooded homes exhibited a three percent decline. Finally, Fruitticher performed two additional linear regression analyses of home sales in two neighboring subdivisions during the same two-year period. According to Fruitticher, because of these subdivisions' close proximity to the subject neighborhood, home values there are driven by the same market forces that drive the values in the subject neighborhood. However, none of the homes in these two subdivisions experienced flooding during the Storm. The linear regression analyses of home sales in these areas reflected an upward trend in values of approximately nine percent.[17] Fruitticher attributes the divergence in market trends between Plaintiffs' neighborhood and the two comparable, nearby communities to the stigma that attaches to properties that have experienced flooding. Fruitticher calculated the percentage decrease in market value due to flood stigma as the difference between the upward trend in the subdivisions outside the stigma area and the downward trend within the stigma area. Thus, according to Fruitticher, the flood stigma has resulted in a 12 percent decline in the value of non-flooded homes in the subject neighborhood and an 18 percent decline in the value of homes that actually flooded. Applying these percentages to the pre-flood market values generated by his multiple regression analysis, Fruitticher concluded that the total stigma damages amount for the subject neighborhood is $9, 034, 000.[18] See ECF No. 77-1 at 94.

         b. Mixed Methodology

         Defendant first argues that Fruitticher's methodology is unreliable because he used a combination of two distinct statistical techniques-multiple regression analysis and linear regression analysis-to calculate Plaintiffs' stigma damages, when he should have analyzed the issue using only one of the techniques, preferably multiple regression analysis. Defendant does not offer any legal support for this argument, nor does it point to any generally accepted standard in the appraisal industry establishing that a stigma damages evaluation should be performed using a single method alone.[19] Defendant's damages expert, Richard Roddewig, testified that when applied properly, both multiple and linear regression analysis are mainstream tools in the real estate valuation industry and that each is an accepted method for determining the effect of a natural disaster, such as the subject flooding, on property values. See also ECF No. 80-1 at 8. Indeed, courts have routinely found that properly constructed regression models can provide reliable support for expert conclusions in a broad range of subjects. See, e.g., Bazemore v. Friday, 478 U.S. 385, 400-01 (1986) (holding that a properly performed multiple regression analysis is an accepted method for determining damages and causation); City of Tuscaloosa v. Harcros Chemicals, Inc., 158 F.3d 548, 566 (11th Cir. 1998) (finding use of multiple regression analysis reliable in antitrust conspiracy case); Cook v. Rockwell Intern. Corp., 580 F.Supp.2d 1071, 1136 (D. Colo. 2006) (admitting expert opinion as to effect of environmental contamination on real property values based on analysis of price trends in comparable markets). An expert's analysis on diminution in value damages has also been admitted when it “incorporated five different, multi-disciplinary approaches” to the question of whether property values in a class area had been impacted by environmental contamination. Cook, 580 F.Supp.2d at 1130 (admitting real estate appraiser's expert opinion as to stigma damages based on combination of real estate market research, review of analogous case studies, analysis of market sales data and information, multiple regression analysis, and review of public opinion surveys). In light of these authorities, the Court finds no grounds for excluding Fruitticher's expert opinion as unreliable simply because it incorporates two statistical methods, provided that each, taken in isolation, contains sufficient analytical rigor to satisfy Daubert.

         In this case, Fruitticher did not, as Defendant asserts, perform “half” of a multiple regression analysis and “half” of a linear regression analysis. Instead, Fruitticher's multiple regression analysis was complete when it generated estimates of the pre-flood market values of homes in the subject neighborhood. His linear regression analysis was complete when it calculated the market trends in the subject neighborhood and in nearby communities during the years before and after the flood. Synthesizing the findings from the two analyses does not render the opinion unreliable. Defendant's expert may disagree with this approach, but the experts' conflicting opinions reveal only a factual dispute, not a flaw in Fruitticher's methodology. Under the circumstances, it would be improper for the Court to pick and choose which variant of the methodology it prefers, to the exclusion of the other. See generally Kumho Tire, 526 U.S. at 153 (stating that if an expert's testimony is within “the range where experts might reasonably differ, ” the jury, not the trial court, should be the one to “decide among the conflicting views of different experts”); Rink, 400 F.3d at 1293 n.7 (observing that “a district court may not exclude an expert because it believes one expert is more persuasive than another expert”). This issue may be explored vigorously through cross-examination, but it does not preclude the admissibility of Fruitticher's opinion. See Quiet Tech., 326 F.3d at 1341 (“[V]igorous cross-examination, presentation of contrary evidence, and careful instruction on the burden of proof are the traditional and appropriate means of attacking shaky but admissible evidence.”).

         c. Multiple Regression Analysis

         Defendant challenges Fruitticher's multiple regression analysis on the ground that, because he cannot explain or manually perform the mathematical calculations that are built into his regression model, his use of the technique amounts to the sort of “black box” damages analysis that several district courts have found unreliable under Rule 702. See, e.g., Open Text S.A. v. Box, Inc., No. 13-cv-04910-JD, 2015 WL 349197, *6 (N.D. Cal. Jan. 23, 2015); Lawrence v. Raymond Corp., No. 3:09-cv-1067, 2011 WL 3418324, at *7-8 (N.D. Ohio Aug. 4, 2011) (stating that experts may not be “a black box into which data is fed at one end and from which an answer emerges at the other”); Fail-Safe, L.L.C. v. A.O. Smith Corp., 744 F.Supp.2d 870, 888 (E.D. Wis. 2010) (rejecting expert analysis that was “in a black box out of the view of the court . . . [because] the court cannot simply take an expert's word for a specific proposition). The Court disagrees. A “black box” expert opinion, as that term is used in the cases cited by Defendant, is one in which an expert's conclusion is stated without any reasoned explanation that would enable the Court, a jury, or an opposing party to meaningfully evaluate the process by which it was reached. See id. Such an opinion is, essentially, an expert's ipse dixit, which the Supreme Court has admonished district courts against admitting into evidence. See Joiner, 522 U.S. at 146 (“[N]othing in either Daubert or the Federal Rules of Evidence requires a district court to admit opinion evidence that is connected to existing data only by the ipse dixit of the expert. A court may conclude that there is simply too great an analytical gap between the data and the opinion.”)(internal citations omitted). In Open Text, for example, the Northern District of California excluded royal rate testimony where the expert failed to “spel[l] out the steps she took to go from the data to the royalty rate opinion” because “the jury [could not] see how the pieces fit together or how the data [drove] the conclusion.” 2015 WL 349197 at *6. The expert's opinion in Open Text was supported only by her professional experience, which is an “abstraction” not “testable in the crucible of cross-examination.” Id.; see also GPNE Corp. v. Apple, Inc., No. 12-CV-02885-LHK, 2014 WL 1494247, at *4 (N.D. Cal. Apr. 16, 2014) (excluding royalty rate testimony where expert “advance[d] no reasoned basis for deriving his $1 per unit royalty from the $86 average net incremental profit” and instead stated that his opinion was based on “all of the evidence in the record” and his “30 years of experience”). Understandably, the court in Open Text found that the expert's opinion was a classic “black box, ” in which she asserted that her proposed royalty rate was reasonable simply because she said so. Id.

         In contrast, Fruitticher's opinion is based on the application of a widely accepted statistical technique to empirical data drawn from the Multiple Listing Service (MLS) and the public property records of Escambia County, Florida. See Tuscaloosa, 158 F.3d at 566 (reversing exclusion of expert testimony based on data compilations and estimated damages that were “the products of simple arithmetic and algebra and of multiple regression analysis, a methodology that is well-established as reliable”). Fruitticher's report describes exactly how he used multiple regression analysis to determine the pre-flood market value of the subject homes and how that determination fits into his overall stigma damages opinion. See ECF No. 77-1. Fruitticher also articulated the precise steps he took to select the independent variables for his model and to confirm the accuracy of its results. Id. Perhaps the best evidence that Fruitticher's multiple regression analysis is not ipse dixit comes indirectly, however, from Defendant's own expert witness, Richard Roddewig. During the Daubert hearing, and also in his 175-page report, see ECF No. 80-1, Roddewig explained, in meticulous detail: (1) the various inputs Fruitticher used in his regression analysis; (2) information that he believed Fruitticher should have included in the analysis, but did not; (3) various problems that he identified in Fruitticher's modeling (e.g., allegedly faulty assumptions); and (4) how and why certain data points used by Fruitticher produced results that were skewed and lacking in statistical significance. Roddewig even explained how, after reviewing Fruitticher's report, he was able to “replicate” Fruitticher's statistical model and “correct” the perceived flaws. Thus, this is clearly not a case where the expert failed to follow any “discernible methodology, ” see GPNE Corp., 2014 WL 1494247, at *4, as Fruitticher's methodology was sufficiently transparent for Roddewig to highlight its myriad alleged deficiencies. Because the Court has already found Fruitticher qualified to testify on the basis of statistical analysis in this case, the fact that Fruitticher “cannot perform the statistical functions personally” does not undermine the reliability of his methodology for admissibility purposes.[20]

         d. Linear Regression Analysis

         Finally, Defendant raises several objections to Fruitticher's linear regression methodology, each premised on inherent principles of statistical analysis that Defendant contends must be satisfied in order for the analysis to be valid. More specifically, Defendant first argues that the explanatory power of Fruitticher's linear regression model, as indicated by its R2 value, is too low for his trend lines to have statistical significance. Second, Defendant argues that Fruitticher failed to remove a statistical outlier from his dataset, which renders the analysis invalid under standard, accepted techniques for performing ...


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