Clearing the Waters: Addressing Misrepresentations in "Clouds in My Coffee" by Precht et al. (2025) Regarding Dredging Sediment Plumes and Coral Reef Damage at PortMiami

Clearing the Waters: Addressing Misrepresentations in “Clouds in My Coffee” by Precht et al. (2025) Regarding Dredging Sediment Plumes and Coral Reef Damage at PortMiami Brian B Barnes1, Ross Cunning2, Peter K Swart3, Rachel N Silverstein4, Andrew C Baker3 1College of Marine Science, University of South Florida, St. Petersburg, FL, USA. 2John G. Shedd Aquarium, Chicago, IL, USA. 3Rosenstiel School of Marine, Atmospheric, and Earth Science, University of Miami, Miami, FL, USA. 4Miami Waterkeeper, Miami FL, USA Correspondence to BBB ([email protected]), RNS ([email protected]) Summary: In the decade since the completion of the PortMiami Deep Dredge Project (PMDP), numerous independent analyses have documented extensive and clear evidence of dredging-related sedimentation and associated degradation of adjacent coral reef habitats. In a new study in the Proceedings of the 24th World Dredging Congress & Exposition, Precht and co-authors attempt to counter these findings and perpetuate their claim that there was only minimal damage to natural resources caused by the PMDP. This review and response document is intended to highlight several misinterpretations, mischaracterizations, and unsupported conclusions presented in that article. In doing so, we reiterate the value of (1) satellites in detecting and quantifying sediment plumes and (2) robust in situ monitoring using effective sediment collection methods, followed by (3) rigorous scientific analyses of these data with the goal of unbiased investigation of dredging-related impacts. In contrast to Precht et al. 2025, multiple publications, reports, datasets, and independent sources — including NOAA (Miller, NOAA staff), Army Corps contractors (Air and Water Research), the Florida Department of Environmental Protection, Miami-Dade County, academic researchers (University of Miami, University of South Florida), and non-profits (Miami Waterkeeper, Shedd Aquarium) — documented severe, project-related impacts on the order of millions of corals killed and hundreds of acres of reef impacted by dredging sediment. These data are further analyzed in Miller et al. (2016), Cunning et al. (2019) and NMFS (2023). Lines of evidence showing significant damage near the dredging channel, compared to pre-project data and northern control sites, include (parentheses indicate data source; note, Mr. Precht was the lead scientist overseeing the Dial Cordy data collection and reports): ● Sedimentation rates and proportion of fines (collected by Dial Cordy) ● Sediment depth (Dial Cordy & NOAA) ● Percent sediment cover (Dial Cordy) ● Coral partial mortality due to sedimentation (Dial Cordy) ● Coral total burial (Dial Cordy) ● Coral density (Dial Cordy) ● Presence/absence of plumes in satellite data (Barnes) No studies were carried out by Dial Cordy on sediment composition either prior to or after the dredging. A report on the mineralogy of samples collected by NOAA after the dredging was complete was provided by Dr. Swart from the University of Miami (Swart 2016). We review and comment on various claims in Precht et al. (2025) below. Claim #1: Satellite data cannot distinguish turbidity associated with dredging from that which is naturally occurring Misunderstandings of the capabilities of satellite remote sensing (and its difference from aerial photography) underlie one of the main assertions made by Precht et al. (2025): “The idea that simply digitizing a satellite image of a turbidity plume and being able to determine an area (polygon) of sediment impacts associated with the PMDP with any accuracy, as calculated by Barnes et al. (2015) is problematic.” While we agree completely with the premise of this quote, the problem is that the beginning of this statement does not accurately reflect the work done by Barnes et al. (2015), which analyzed over a decade of multispectral satellite data to compare observations made during the PMDP to those prior to dredging activities. Specifically, Barnes et al. (2015) focused on red light reflected by the water column offshore of PortMiami, quantified as the remote sensing reflectance at 667 nm (Rrs667, in sr-1). Notably, suspended sediment strongly reflects this red light, while other water column constituents (phytoplankton, dissolved organic matter) do not. Thus, the workflow included: 1. Compare Rrs667 for each satellite pixel in 2013-2015 to its historical precedent (2002-2012). 2. Outline where satellite true color composites show obvious plumes (e.g., Fig. 1) and / or Rrs667 positive anomaly. Include 10 months before dredging as comparison. 3. Analyze multiple environmental conditions (windspeed, tidal stage, etc) to identify those corresponding to the highest Rrs667 values pre-dredging. Remove these “normal plumes” from analysis and calculate the 90th percentile in Rrs667. 4. Use this 90th percentile to ‘validate’ the plume delineations. 2/3 of all plume-identified pixels showed ‘true’ anomalies (>90th percentile in pre-dredging conditions). Figure 1: True color satellite composites from Landsat-8 showing Miami plumes (left) without dredging and (right) during dredging. The top row includes images collected near high tide (measured at Virginia Key), while the bottom images were collected near low tide (all were within 25 minutes of the H/L). In the absence of dredging, ebb-tidal plumes generally appear faint green/brown, and are very difficult to visually detect (panel b). During dredging, however, PortMiami plumes were readily apparent (bright white in color; c, d), and regularly occurred even in the absence of an ebb tide (e.g., panel c). Notably, in the 10 months prior to dredging, we identified only 7 plumes at PortMiami in the MODIS/Aqua satellite record (near-daily repeat sampling). In contrast, during the ~17 months of dredging, plumes were observable in 111 MODIS/Aqua overpasses. Additionally, Precht et al. (2025) argue that “[f]urther confounding an understanding of turbid plumes present during the PMDP are oceanographic conditions such as wave height and current flow.” Notably, the words/phrase “wind,” “tide,” “tidal,” and “environmental conditions” appear a total of 91 times in Barnes et al. (2015). Extensive effort was made to identify environmental conditions which might explain plumes in the absence of dredging (Figures 5-8 in Barnes et al. (2015)). Turbidity plumes associated with these environmental conditions were removed from trend analyses, as were any pixels where insufficient multispectral data were available (Fig. 2). Figure 2: Estimated area (km2) of plumes determined from MODIS (blue) and Landsat (red). Data with reduced certainty due to environmental conditions favoring high Rrs667 (Env. Flag) and/or delineations based on RGB-only data (i.e., true color composite) shown with ‘+’ and ‘×’ symbols, respectively. The vertical bar indicates the beginning of dredging. From Barnes et al. (2015). As noted above, reticence to recognize satellite observations as useful in monitoring dredging plumes may be due to an incomplete understanding of the capabilities of satellite data. This may be partially driven by how satellite ocean color data are often presented. In both publications and in the press, satellite ocean color data are often shown as ‘true color’ RGB composites - images that appear as if taken from an orbiting smartphone. In reality, ocean color satellites are far more advanced in both design and sensitivity. Traditional cameras measure only three ‘colors,’ each typically with ≥50 nm bandwidth, meaning every pixel will include one single measurement of ‘red’ light. Ocean color sensors have dozen(s) of ‘wavebands,’ typically with ≤10 nm bandwidth. These wavebands are specifically placed to capture the spectral signal of a particular atmospheric / water column constituent. For example, the Ocean and Land Colour Instrument (OLCI) collects six different ‘red’ measurements: for quantification of sedimentation, chlorophyll-a absorption, and atmospheric oxygen absorption, as well as three separate measures of chlorophyll-a fluorescence. Satellites also repeatedly measure the same locations in the exact same manner for years or even decades, which means any satellite image may be placed in the context of measurements collected before or (eventually) after. As such, satellite data can be used to calculate the natural variability for a specific location, from which anomalies may be quantitatively identified. Even in a qualitative context, coarse- resolution and high-resolution satellite images show a clear difference between ‘natural’ turbidity plumes in the PortMiami region and those observed during the PMDP dredging (Fig. 1). Several of the references used by Precht et al. (2025) to bolster their questioning of satellite data utility for assessment of dredging plumes (Claim 1) do not appropriately characterize these capabilities, even if the original authors were clear on this point. For example, Precht et al. (2025) states: “Puckette (1998) described attempts to use remote imagery to track plumes associated with dredging in the Cape Fear River near Wilmington, North Carolina. He noted they were unsuccessful because the naturally turbid waters in the vicinity of the dredge obscured the plume.” However, for this discussion, Puckette (1998) was describing analysis of aerial imagery (i.e., traditional camera photographs). In the same section, Puckette (1998) counters that: “Research has shown that it is possible to measure sediment discharges associated with rivers in a quantitative manner using multispectral imaging techniques (Gradie et al. 1995) … [M]ultispectral imagery can in most cases distinguish sediment plumes in areas with high ambient turbidity. Even with limited application of multispectral techniques to monitoring of dredge-related sediment plumes, the technique may prove useful in identifying plume location and the extent of a plume.” Indeed, quantitative estimation of TSS from satellite data is well established, and the science and satellite instrumentation have evolved greatly since Puckette’s observations 27 years ago. In a review paper that is now almost ten years old, Dorji and Fearns (2016) compared performance of 76 different TSS algorithms, highlighting the breadth of research on derivation of TSS from satellites. The validated performance of these approaches was generally quite strong (R2 > 0.8). Similar misunderstandings by Precht et al. (2025) also underlie mischaracterization of others’ conclusions as valid in the assessment of PMDP plumes. For example, Orpin and Redd (2012)’s findings were summarized by Precht et al. (2025) as: “While visually spectacular, satellite and aerial images offer limited quantitative information of total sediment load carried by turbid plumes.” Despite similarities in verbiage, the penultimate word used by Precht et al. (2025) differs from that originally written by Orpin and Redd (2012): “While visually spectacular, satellite and aerial images offer limited quantitative information of total sediment load carried by hypopycnal plumes, as many of these plumes may contain algal blooms but relatively low concentrations of suspended sediment (ca. <5 mg/l)” Through this rewording, Precht et al. (2025) conflates ‘turbid plumes’ occurring during PMDP with those specified as Orpin and Redd (2012) as having “low concentrations of suspended sediment (ca. <5 mg/l).” As part of this discussion, Precht et al. (2025) correctly state that it is difficult (or even impossible) to separate the individual contributions of a ‘natural plume’ and those from dredging-related suspended sediment (co-occurring within the plume) in a single image. Their use and labeling of their Figure 2, however, does just that. Specifically, Precht et al. (2025) note that 2 distinct plumes can be seen in this image, and argue without evidence that the nearshore plume is a “Discharge Plume of [the] Miami River,” adding that “this plume includes a mixture of sediment-laden, nutrient-rich, and highly polluted discharge of the Miami River.” However, closer inspection of this satellite image (their Figure 2 is replicated in Fig. 3) reveals an additional dredge & barge that can be seen operating near the jetties. Furthermore, there is no milky white plume leaving the Miami River, crossing Biscayne Bay and exiting Government Cut. Rather, Miami River discharge has no obvious color in this specific image. Longer time series of satellite data indicate that Miami River discharge, if present, generally appears darker in satellite images (e.g., Fig. 1b), likely due to the presence of phytoplankton and dissolved organic matter. Figure 3: Maxar satellite imagery (14 December 2015) which contextualizes the data shown in Figure 2 of Precht et al. (2025). The dotted white square in the bottom right of the image is the extent originally shown, within which two distinct plumes were labeled: “Discharge Plume of Miami River” and “Dredge Plume.” However, within this image, a dredge and barge are clearly observable working within Government Cut (red square, zoomed-in on top right panel), contributing sediment load to the plume improperly labelled “Discharge Plume of Miami River.” Expanding this same satellite image to the west (bottom left), it is clear that the Miami River outflow does not share the ‘milky white’ color (indicative of suspended sediments) as seen in the downstream waters. There is no visible milky plume travelling from the Miami River, across Biscayne Bay, and offshore on the reef areas. Instead, moving offshore from the Miami River mouth, the first appearance of obviously ‘milky’ sediment plumes coincides with construction activities on the southwestern side of Dodge Island (purple square, zoomed-in on top left). Claim #2: Wave-driven resuspension was the driving factor in observed sedimentation Despite rigorous statistical analyses demonstrating relationships between satellite-observed plumes, sediment accumulation, benthic sedimentation, coral burial, and coral mortality (Cunning et al. 2019), Precht et al. (2025) assert: “Based on a post hoc analyses of coral colonies affected by sediment accumulation, daily sedimentation rates, and percent cover of sediment on the substrate at the PortMiami channel and control monitoring sites, we determined that wave driven sediment resuspension was the major factor in the number of colonies experiencing sediment stress (see Figures 5 – 7).” [emphasis added] In arguing this point, Precht et al. (2025) include several line graphs (their Figures 5-7) showing wave height and sedimentation rates. Based solely on visual interpretation of these plots (and lacking statistical analysis), Precht et al. (2025) invite readers to “note the strong correlation between wave heights and sediment deposition” (Precht et al. 2025, discussing Figure 5). However, no statistical analyses were offered, no correlation coefficients were provided, and no other variables were rigorously considered - yet these plots were considered sufficient evidence for the authors to conclude the singular causative impact of wave-driven resuspension on sedimentation. To more rigorously assess the merit of the claimed relationships, we digitized the data points in Precht et al. (2025)’s Figures 5-7 and created scatterplots from which we could calculate the correlation coefficients (Figs. 4, 5). Broadly, these analyses indicated only weak to moderate correlations. For example, using the data in Figure 5 of Precht et al. (2025), the correlation coefficient (R) between wave height and coarsegrain sedimentation was 0.69 for the control traps and 0.68 for the channel traps (Fig. 4). While these values indicate moderately strong correlation, much of this statistic is driven by a single point with wave height >20% higher than all other values. Such outliers should be treated with caution in correlation analyses, particularly with a limited data quantity. Removing this outlier (top right point in Fig. 4), R drops substantially to 0.52 (control traps) and 0.59 (channel traps) - hardly a “strong correlation.” Figure 4: Scatterplot displaying digitized data from Figure 5 of Precht et al. (2025). While Precht did not statistically analyze these data, we digitized them and calculated correlation coefficients. For the entire dataset, R = 0.69 for the control traps and 0.68 for the channel traps. Excluding the outlier with windspeed > 20% higher than all other values in this dataset, R drops to 0.52 (control traps) and 0.59 (channel traps). Continuing this line of reasoning, Precht et al. (2025) assert that fine sediments similarly show a correlation with wave height, albeit with a “temporal lag.” The justification for such a lag is stated as: “increases in fine grained sediments in the traps (Figure 6) are associated with deposition during the waning periods following storms (Verspecht and Pattiaratchi 2010).” Given that the data included in this analysis were aggregated at the monthly scale, the role of individual storms (as discussed in Verspecht and Pattiaratchi (2010), 1-5 days in duration) should be substantially muted. Even taking this reasoning at face value, however, the actual data do not strongly support the conclusion of a lagged correlation. Specifically, with no lag, R = 0.66 for control sites and 0.32 in the channel. With a 1 month lag, there is essentially no change in the correlation coefficient at the control sites (R = 0.67) and a minimally stronger relationship (R = 0.46) for channel sites (Fig. 5a). Finally, in discussing Figure 7, Precht et al. (2025) directs readers to “note the correlation between wave height and sediment accumulation” on coral colonies. Derived R for these relationships were very low and negative: -0.30 (control sites) and -0.12 (channel) (Fig. 5b). Lagged correlations are also weak, with maxima of R ≈ 0.5 at 8 weeks lag. Curiously, the data as presented in Figures 5-7 also appear incompatible - weekly mean wave height data never exceeded ~1.4 m (the top value is 4.7 ft in Fig. 7), yet the monthly averaged values had a maximum of ~1.55 m in November of 2013 (see Figs. 5-6). Figure 5: Scatterplots displaying data from (a) Figure 6 and (b) Figure 7 of Precht et al. (2025). Since the authors did not statistically analyze the relationships, we digitized the data and conducted correlation analyses here. The authors argue that data show a lag between mean wave height and sedimentation rate, but this is unsupported by the data - while a 1-month lag showed the “best” correlations (R = 0.67 for control sites and R = 0.46 for channel sites; panel a), these are not particularly strong relationships nor substantially different than for non-lagged correlations. For panel (b), Precht et al. (2025) argue that there is a correlation between wave height and sediment accumulation, but the derived relationships are very weak and negative: R = -0.30 (control sites) and -0.12 (channel). While we have striven to provide statistical measures missing from Precht et al. (2025), it is worth reiterating the classic adage that correlation is not causation. Simply looking at the datasets presented, the strongest correlations observed among ANY datasets were between fineand coarse-grained sedimentation rates measured at the same locations (R = 0.76 for control sites, R = 0.74 for channel sites). This, of course, belies the argument that these data show sedimentation of fines lags that of coarse materials - a claim that was made with far lower statistical basis. Moreover, even if the data presented in Precht et al. (2025) showed “strong correlations” as claimed, this does not indicate singular causative impact of wave height on sedimentation nor rule out any other factors (e.g., the ongoing dredging). Indeed, these same sediment trap data (Cunning et al. 2019), satellite observations (Barnes et al. 2015), and even subsequent discussions in Precht et al. (2025) highlight strong relationships between sedimentation (or plumes detectable in satellite data) and distance to channel. Moreover, this relationship is clearly observable in Figs. 4, 5, as control trap sedimentation was almost always lower than at the channel-side sites (and see Claim 3). More specifically, based on the data included in Precht et al. (2025), for months with low wave heights (< 0.8 m), total sedimentation (i.e., sum of coarse and fine) at the control sites was always quite low (mean = 0.07 g d-1), but channel-side sedimentation was nearly 7 times higher (0.44 g d-1). For the months with higher wave heights, total sedimentation was ~2 times higher near the channel (1.16 g d-1) than at the controls (0.60 g d-1). In total, while higher wave heights increased sedimentation throughout the region, average surplus sedimentation at the channel (defined as channel minus control; 0.48 g d-1) was larger than the overall average control sedimentation (0.375 g d-1). Overall, the evidence presented in Precht et al. (2025) does not convincingly support the conclusion that resuspension was the driving factor in observed sedimentation. Moreover, the contention that “failure to consider resuspension and deposition due to seasonal variation in wave heights is a critical flaw in both [Cunning et al. (2019)’s] analysis and conclusions (see Figure 6),” is logically flawed and unsupported. Wave action and season would affect both control site and channel-side sites, therefore this was considered in the comparison between channel-side and control sedimentation rates. The simple fact that channel-side sites consistently showed higher sedimentation than control sites (Figs. 4, 5) is clear evidence of the role dredging played in observed sedimentation. Claim 3: Dredge position was not the driving factor influencing sedimentation As part of this discussion, and without providing any plots or data, Precht et al. (2025) assert that the position of the dredge (“moving from west to east” during the PMDP) was misaligned with the relative timing and location of peak sedimentation. This conclusion countered their “a priori expectation that … a greater concentration of sediments [would be found] in traps closest to active dredge operations,” and therefore “dredge activity was [not] the primary influence on the flux of sediment in the traps.” Again, this claim was provided without statistical analysis or proper operationalization of the terms. For example, was the dredge intensity the same at all sites? Did the dredge spend equal time at all sites? How were the trap data binned for this analysis (all other analyses only split data into “channel” and “control” traps, not in a cross-shore direction)? How was “position of dredge” analyzed? Were GPS coordinates (which are available) inputted? Did the dredged material differ along with the “position of the dredge.” Given these considerations, the a priori expectation is not as simple as stated. For example, dredging activities extended well inshore of the westernmost sediment traps (no traps were inside the Government Cut jetties), meaning the minimum distance between dredging and the nearest sediment trap varied greatly through time. Furthermore, as shown in Fig. 3 (red zoom-in box) and Fig. 2d, dredging activities within the Government Cut jetties can distribute sedimentation to ‘offshore’ locations. Fig. 3 also shows dredging operations occurring simultaneously at both ends of the channel, meaning a metric of dredge position moving from “west to east” certainly does not capture the entirety of the dredging operations. Most importantly, however, no control variable or baseline (e.g., pre-dredging) was considered in Precht et al. (2025)’s analysis of dredge position and sedimentation. In contrast, Cunning et al. (2019; Fig. 6) used much of the same data with rigorous statistical analyses to identify extreme increases in sediment cover on the benthos—up to 90%—coinciding with the start of dredging. Sediment cover decreased with increasing distance from the dredging site, indicating that proximity to the channel was a highly significant factor. Sedimentation rates began to drop after dredging ended — another strong indication that dredging was the source of sedimentation. However, sediment cover still remained elevated above background/control levels even one year later. This suggests that substantial sediment remained on the benthos but was no longer being resuspended into the traps, further supporting the conclusion that dredging—not natural resuspension—was the primary driver of the observed increases in sedimentation. Additionally, control sites provide a proxy for resuspension rates and background sedimentation, which was low, particularly for “fines.” This does not support the finding that resuspension was the driving factor in sedimentation rate, particularly at locations near the channel to the north where the current pushed the majority of the sediment. Figure 6: Accumulation rates of fine sediment throughout PMDP. Horizontal line segments indicate measured rates of fine sediment accumulation. Smooth lines are Global Additive Model fits (± 95% confidence interval), colored according to distance from channel. Vertical dotted lines indicate the beginning and end of dredging operations. Horizontal dashed line indicates 25 mg cm-2 d-1. Sediment deposition rates exceeding this threshold over 30 days may cause severe coral stress leading to mortality (Nelson et al. 2016). From Cunning et al. (2019). It is worth additionally noting that even Precht et al. (2025) explicitly cites both modeling exercises and in situ observations that “most of the sediment impacts related to the project were observed directly adjacent to the dredge channel and diminished as one moved away from the project area (DCA 2015[a], Figure 11).” This contradiction makes their conclusion as to the singular impact of wave height both illogical and unsupported. Indeed, Cunning et al. (2019) shows the correlation with distance from channel quantitatively (Fig. 7): “...over the 20 months of sediment trap monitoring, this threshold [for coral stress and mortality] was exceeded, on average, 84.0% of the time at sites adjacent to the channel, 66.7% of the time at intermediate distance sites (1.25–2.5 km), and 15.2% of the time at the farthest sites (9.4 km; Fig. 4). As some of this sediment deposited on the benthos, reef habitat initially low in sediment cover became 50–90% covered in sediment during dredging operations (Fig. 6) ... As the benthos became covered in sediment, corals were In summary, Precht et al. (2025) argue that rock chopping does not purposefully generate rock flour through grinding / pulverization, and that reducing the number of cuts made into the rock thereby reduces the amount of fine sediments released. This logic ignores the underlying contentions by the Army Corps of Engineers (2018, 2020) that rock chopping causes multiple suspension events of fine sediments (including rock flour already within the rock) which occur during the entire interval from the initial rock chopping through to the eventual removal of these spoils using a clamshell dredge. Note that Fig. 3 clearly shows clamshell dredging contributed sediment to the plumes occurring during the PMDP, although it is unclear whether the dredging activity on that date was collecting the rock chopping spoils. Claim 9: “No project related sediment was ever observed at any of the southern control monitoring sites.” This is a demonstrably false statement. Multiple lines of evidence demonstrate project-related sedimentation at the southern control sites: 1) Total sediment accumulation at southern control sites (located 1.25-2.5km from the channel) were higher than the control sites 9.38 km to the north. 2) Swart (2016) detected sediment types atypical of reef sediment at the southern control site. 3) Cunning et al. (2019) detected trends in sediment deposition at southern control sites that were similar over time to the deposition at channelside sites, indicating a likely origin from dredging. Summary Precht and colleagues, in a manuscript published in the Proceedings of the 24th World Dredging Congress & Exposition, attempt to disprove or discredit numerous independent studies, datasets, and peerreviewed publications, all of which demonstrate overwhelming evidence of widespread dredging-related impacts on the reefs adjacent to the PortMiami shipping channel. To plausibly accomplish this, Precht et al. (2025)’s counter-interpretation would need to present new, statistically robust analyses of supporting data, and a compelling alternative theory to explain how the reef around the dredging channel became covered in sediments that did not originate from the nearby dredging project. Precht et al. (2025) presents none of these. Precht et al. (2025)’s analysis is flawed in that it: 1) fails to perform statistical analyses; 2) sets up “straw man” arguments — framing the issue in oversimplified or misleading terms that mischaracterize the issue — and then dismisses these assumptions and draws false conclusions; 3) improperly interprets the data, with no or few spurious analyses; 4) attempts to discredit studies by highlighting minor or non-critical issues or by entirely misinterpreting and/or misrepresenting their analyses. In short, nothing presented in Precht et al. (2025) disproves the findings that the PortMiami dredging project caused hundreds of acres of reef to be buried and likely millions of corals to be killed. The science is clear: the harm caused to the reef and corals by the dredging project was catastrophic. Upcoming dredging planned for Port Everglades would be “largest impact to coral reefs permitted in U.S. history” (NMFS, 2024), with an estimated 10 million corals within the impact monitoring area (Cunning et al. 2025). We also now know that these include some of the last naturally occurring staghorn corals left in Florida (Manzello et al. 2025). With this context, in one respect we strongly agree with Precht et al. (2025) — it is important that the right lessons are learned from the PortMiami dredging project. Indeed, one lesson correctly identified by Precht et al. (2025) is the need to “reduc[e] the permitted overflow of fine-grained sediment contained within the slurry from dump scow loading and transport." Additionally critical to address, however, are issues related to monitoring surveys, mitigation protocols, and minimization measures for reducing dredging-related impacts in real time. Moreover, the procedures for selecting and overseeing the contractors responsible for monitoring environmental impact and the methods used for collecting, managing, reporting, and analyzing data must be revisited. So, while lessons learned from the PortMiami Dredging Project must guide implementation of best management practices for future projects, these lessons should be rooted in rigorous science rather than the enigmatic “clouds in my coffee.” References: Bak, R. P. M., and Meesters, E. H. (2000). Acclimatization/adaptation of coral reefs in a marginal environment. Proceedings Ninth International Coral Reef Symposium, Bali, Indonesia (pp. 23-27). Baker, A. (2018). Public comments. Miami Harbor Navigation Improvement Study Public Meetings, Port Miami, Miami FL (November 7, 2018). 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