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Correction to: Nature Ecology & Evolution https://doi.org/10.1038/s41559-019-0970-7, published online 2 September 2019.The Journal would like to note that the authors first made contact in September 2019 to raise the concerns that follow, and the Journal apologizes both for the delay in relaying these corrections publicly and for the changed instances that prevent making corrections to the original article itself. What follows is the Author correction.In the version of this article initially published, we made several errors in our R analysis code, and in the text and figures. First, the number of species with negative net dispersal velocity (net DV) were incorrectly calculated, resulting in slight changes in Fig. 2 and Supplementary Fig. 6, and in the text. The amended figures are provided below (Figs. 1–7). Changes to the text under the ‘DVs’ subsection of Results are: “When considering the mainstem pathway, we estimate that the mobile subpopulations of 134 (old version: 124) and 185 (old version: 174) (RCP 4.5 and 8.5, respectively) species will experience dispersal deficits in at least 50% of their southern Appalachian range, whereas these estimates increase to 229 (old version: 226) and 231 (old version: 232) species for the stationary subpopulation. Slow-climate-velocity tributaries reduce the number of species experiencing dispersal deficits by 99.3% (old version: 99.2%) and 90.3% (old version: 16.9%) (RCP 4.5 and 8.5, respectively) for the mobile component and 17.9% (old version: 90.8%) and 12.1% (old version: 12.9%) for the stationary component (Fig. 2a,b).” The two large discrepancies in dispersal deficit values (90.3% vs. 16.9%; 17.9% vs. 90.8%) were solely consequences of original text errors (16.9% and 90.8% values were erroneously switched), and not differences in calculations; therefore, the results did not change.Fig. 1Figure 2, original and corrected.Full size imageFig. 2Figure 3c,d, original and corrected.Full size imageFig. 3Figure 4, original and corrected.Full size imageFig. 4Figure 5, original and corrected.Full size imageFig. 5Supplementary Figure 6, original.Full size imageFig. 5Supplementary Figure 6, corrected.Full size imageFig. 6Supplementary Figure 8, original.Full size imageFig. 6Supplementary Figure 8, corrected.Full size imageFig. 7Supplementary Figure 9, original.Full size imageFig. 7Supplementary Figure 9, corrected.Full size imageSecond, we made errors when plotting Fig. 3c,d. Boxplots of mean change in habitat suitability were plotted instead of median change as specified in the caption; further, whiskers did not include the entire range of values. The amended figure is provided below. We would like to correct associated errors in text; specific changes are: “Our ENMs estimate a median 15.1% (old version: mean 14.1%) reduction (range −42.5% to +16.6% [old version: −51.6% to +2.4%] across 233 species) in habitat suitability associated with the tributary pathway compared with only a 3.8% (old version: 1.6%) reduction (−11.0% to +12.3% [old version: −7.9% to +1.8%]) for the mainstem pathway due to differing non-temperature habitat conditions (Fig. 3a,b).”Third, we made errors when plotting Fig. 4 and Supplementary Fig. 8. Specifically, net DV values were incorrectly rescaled; one extinct species was erroneously included in the plot; and the number of species in each quadrant was counted incorrectly. The amended figures are shown below. We would like to add a sentence (“The y-axes are inverse hyperbolic sine (asinh)-transformed”) to the caption of Fig. 4 to describe the y-axis scaling in the amended figures. There were two other text errors in the caption. The phrase “Mean net DV” should have been “Median net DV,” whereas the phrase “mean habitat suitability” should have read “median change in habitat suitability.” Therefore, the corrected Fig. 4 caption should read: “Species-level mismatch between net DV and upstream habitat suitability. a–d, Median net DV of mobile (a,b) and stationary subpopulations under the RCP 8.5 scenario plotted as a function of median change in habitat suitability for mainstem (a,c) and tributary (b,d) dispersal pathways. Each point represents a species and is computed as the median response across all projected occupied reaches. Red and blue numbers correspond to the number of species in each of the four quadrants. The y-axes are inverse hyperbolic sine (asinh)-transformed. e–h, Four species highlighting the diversity in dispersal-based and habitat suitability-based vulnerability: streamline chub (e); brook trout (f); flathead catfish (g); blacknose dace (h). Credit: David Neely (e–h)”. These corrections did not change our inferences.Fourth, there were errors in rescaling and plotting net DV values and in the calculation of quadrant percentages in Fig. 5 and Supplementary Fig. 9. The amended figures are shown below. We would like to add two sentences at the end of Fig. 5 caption to provide greater detail on plotting methods: “The y-axes of the scatterplots are inverse hyperbolic sine (asinh)-transformed. For clarity, the scatterplots show net DV values ≥ −13,000 and ≤ 130, and change in habitat suitability values ≤ 100, representing >99.5% of all observations.” There was one other text error in the caption: the phrase “mean habitat suitability” should have read “mean change in habitat suitability.” Therefore, the corrected Fig. 4 caption should read: “Community-level mismatch between net DV and upstream habitat suitability. a–d, Mean net DV of mobile (a,b) and stationary (c,d) subpopulations under the RCP 8.5 scenario plotted as a function of mean change in habitat suitability for mainstem (a,c) and tributary (b,d) dispersal pathways. Each point (scatterplot) and reach (map) is computed as the mean response for all species projected to occur within the reach. Quadrant numbers represent percentage of reaches in the quadrant. Colours associated with the upper-right quadrant correspond to ‘safe’ reaches where community members can keep pace with ISVs and habitat suitability increases. Colours associated with the lower-left quadrant correspond to ‘vulnerable’ reaches where community members cannot keep pace with ISVs and habitat suitability declines. The y-axes of the scatterplots are inverse hyperbolic sine (asinh)-transformed. For clarity, the scatterplots show net DV values ≥ −13,000 and ≤ 130, and change in habitat suitability values ≤ 100, representing >99.5% of all observations.” These corrections did not change our inferences.Fifth, there was an error in the last sentence of the “Calculating net DVs” subsection in Methods: “Last, we calculated the mean net DV for each species (species-specific DV) by averaging net DVs at all occupied reaches, as well as the community-wide net DV at each stream reach (reach-specific DV) by averaging the net DVs of all species at each reach.” This sentence should have read “Last, we calculated the median net DV for each species (species-specific DV) across all occupied reaches, as well as the mean community-wide net DV at each stream reach (reach-specific DV) by averaging the net DVs of all species at each reach.”Corrections of calculation errors yielded results that were similar to those in the original analysis whereas corrections of plotting and text errors did not affect our original inferences. Therefore, these errors did not change the overall results and conclusions of the article. We sincerely apologize for any misunderstanding and inconvenience caused by these errors. More

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Long-term acoustic data collectionPassive acoustic monitoring was conducted from November 19, 2018 to October 3, 2020, with 683 days of recording effort overall (Supplementary Table 2), using a High-frequency Acoustic Recording Package (HARP)37. The HARP was deployed in Bahía Norte, Guadalupe Island, located approximately 150 miles offshore of México’s Baja California Peninsula (Fig. 1). The HARP was bottom-mounted and deployed to a depth of approximately 1100 m, with a calibrated hydrophone suspended ~30 m above the seafloor. The same hydrophone was used for both deployments to facilitate data comparison. The omnidirectional hydrophone sensor (ITC-1042, International Transducer Corporation, Santa Barbara, CA) had an approximately flat (±3 dB) hydrophone sensitivity from 10 Hz to 100 kHz of −200 dB re V/μPa. The sensor was connected to a custom-built preamplifier board and bandpass filter. The calibrated system response was corrected for during analysis. Data were sampled continuously at a 200 kHz sampling rate with 16-bit quantization, effectively monitoring a frequency range of 10 Hz–100 kHz.Automatic detection and manual classification of beaked whale echolocation clicksBeaked whales can be acoustically identified by their echolocation clicks38. These signals are frequency-modulated (FM) upswept pulses, which appear to be species-specific and are distinguishable by their spectral and temporal features. Cuvier’s beaked whale echolocation signals are well differentiated from the acoustic signals of other beaked whale species. They are polycyclic with a characteristic FM pulse upsweep, peak frequency around 40 kHz, and uniform inter-pulse interval of about 0.4–0.5 s39,40. Additionally, Cuvier’s beaked whale FM pulses have characteristic spectral peaks at approximately 17 and 23 kHz.Beaked whale FM pulses were detected in the HARP data with an automated method using the MATLAB-based (Mathworks, Natick, MA) custom software program Triton (https://github.com/MarineBioAcousticsRC/Triton) and other MATLAB custom routines. After all potential echolocation signals were identified with a Teager–Kaiser energy detector41,42, an expert system discriminated between delphinid clicks and beaked whale FM pulses. A decision about presence or absence of beaked whale signals was based on detections within a 75 s segment. Only segments with more than seven detections were used in further analysis. All echolocation signals with a peak and center frequency below 32 and 25 kHz, respectively, a duration less than 355 μs, and a sweep rate of More