Ecology

Study subjects and measurement of skin physiological parametersWe analyzed skin microbiome and mycobiome from cheeks and foreheads of healthy younger (19–28 years old, Y-group) and older (60–63 years old, O-group) Korean women who were free from cutaneous disorders (Table 1 and Supplementary Table S1). All 61 subjects had been living in Seoul, Korea, for more than 3 years with normal skin conditions. We preferentially selected those who had sebum secretion greater than 30 arbitrary units and moisture greater than 50 arbitrary units in both groups. Among the measurements of moisture content, pH, sebum content, and transepidermal water loss (TEWL), only sebum and TEWL decreased significantly in the O-group compared to the Y-group in the cheeks (P = 2.25e−06, Wilcoxon rank-sum test; P = 0.019, Welch two-sample t test) and forehead (P = 1.33e−06, Wilcoxon rank-sum test; P = 0.003, Welch two-sample t test). Whereas no significant differences were found in the average values for moisture (cheeks: Y-group, 59.9; O-group, 56.6; forehead: Y-group, 61.1; O-group, 58.7) and pH (cheeks: Y-group, 6.0; O-group, 5.8; forehead: Y-group, 6.0; O-group, 5.6) between the two age groups.Table 1 Characteristics of subjects for aged related skin microbiome and mycobiome study.Full size tableComparisons in cheek and forehead microbiome and mycobiome between the two age groupsWe analyzed bacterial communities from 27 Y-group samples (cheeks, n = 13; forehead, n = 14) and 24 O-group samples (cheeks, n = 12; forehead, n = 12) and fungal communities from 28 Y-group samples (cheeks, n = 15; forehead, n = 13) and 32 O-group samples (cheeks, n = 16; forehead, n = 16), except for samples that were eliminated from the Illumina Mi-Seq sequencing due to low sequence reads (bacteria,  3. 0) (Fig. 4). Pathways belonging to the metabolism category were dominant in each age group. In the cheek of the Y-group, pathways involved in energy metabolism by bacteria, such as glycolysis/gluconeogenesis, citrate cycle, pentose phosphate pathway, fructose and mannose metabolism, galactose metabolism, d-alanine metabolism, and thiamine metabolism, were predominant, whereas in the cheek of the O-group, degradation-related pathways, such as fatty acid degradation, synthesis and degradation of ketone bodies, benzoate degradation, and chloroalkane and chloroalkene degradation, were predominant. In the forehead of the Y-group, glycolysis/gluconeogenesis, pentose phosphate pathway, fructose and mannose metabolism, galactose metabolism, d-glutamine and d-glutamate metabolism, d-alanine metabolism, and thiamine metabolism pathway were significantly more abundant, whereas in the forehead of the O-group, fatty acid degradation, synthesis and degradation of ketone bodies, valine/leucine and isoleucine degradation, and limonene/pinene degradation pathway were significantly more abundant.Figure 4Heat map for significantly different predicted functional pathways on (a) cheeks and (b) foreheads of Korean women by age based on LEfSe analysis (LDA score  > 3.0).Full size imageThe metabolism pathway for biotin, a water-soluble vitamin that is effective for skin health and essential for keratin production15, was more prevalent in the cheek and forehead of the Y-group. Interestingly, the metabolism pathway for lipoic acid, which is known to possess beneficial effects against skin aging and is used widely in cosmetic and dermatological products16,17, was significantly higher in the foreheads of the Y-group. We tracked the specific ASVs possessing these pathways, in both biotin metabolism and lipoic acid metabolism, Cutibacterium sp. (ASV2136 and ASV2130) and Staphylococcus sp. (ASV3008) were predicted to have the top three relative abundances in KOs. The relative abundances in biotin metabolism and lipoic acid metabolism of Cutibacterium sp. (ASV2136) were 24.9% and 26.1%, respectively. The relative abundances for each pathway for Staphylococcus sp. (ASV3008) were 10.2% and 18.7%, and for Cutibacterium sp. (ASV2130), they were 9.3% and 10.0%, respectively. We confirmed these two pathways in the genome of skin bacteria, C. acnes (Supplementary Fig. S2). These additional analyses support the reliability of the function in the skin environment of Cutibacterium. Interestingly, from the LEfSe result, Cutibacterium sp. (ASV2136) had a significantly higher abundance in the cheek and forehead microbiome of the Y-group. The pathway of biosynthesis of lipopolysaccharide, also known as bacterial endotoxins, showed higher abundance in the cheek and forehead microbiome of the O-group. The ASVs that contribute to inferring the LPS biosynthesis pathway were identified as Paraburkholderia sp. (ASV5030) and B. vesicularis (ASV4155). Also, pathways related to antibiotic biosynthesis (biosynthesis of vancomycin group antibiotics) and bacterial motility (bacterial chemotaxis and flagellar assembly; both belonging to the cellular processes category) were prominent in the cheek and forehead of the O-group. PICRUSt2 analysis implied that, regardless of skin site differences, the potential functions of the microbial community that compose the skin microbiome were similar according to age.Network analysis on cheek and forehead microbiome and mycobiomeWe performed SParse InversE Covariance estimation for Ecological Association Inference (SPIEC-EASI) analysis to evaluate the overall network of the skin microbes. The results of network density (D) on 81 cheek and 87 forehead ASVs, calculated using the ratio of the number of edges, showed higher network density in the skin microbiome of the Y-group (D = 0.015 and D = 0.001, in cheek and forehead, respectively) than the O-group (D = 0.007 and D = 0.007, respectively) (Fig. 5). To examine network correlation between bacteria and fungi, network density for Bacteria–Fungi (DBF) was calculated by the actual number of edges and a potential number of edges in a correlation ([bacterial nodes × fungal nodes]/2). We confirmed higher network density in the cheek of the Y-group (DBF = 0.008) than the O-group (DBF = 0) and edges of the major bacterial and fungal taxa, such as Staphylococcus sp. (ASV3008)—M. sympodialis (ASV500) and Roseomonas sp. (ASV4088)—M. restricta (ASV482), were observed in the cheek of the Y-group. In the forehead, edges of Methylobacterium sp. (ASV4314)—M. globosa (ASV454), Methylobacterium sp. (ASV4314)—Zygosaccharomyces rouxii (ASV208), and Venionella sp. (ASV3575)—M. sympodialis (ASV500) were observed in the Y-group, and edges of Cutibacterium sp. (ASV2107)—M. globosa (ASV461), Staphylococcus sp. (ASV3024)—M. arunalokei (ASV446), and Methylobacterium (ASV4314)—M. dermatis (ASV448) were observed in the O-group (DBF = 0.004). We found a network between bacteria and fungi with different kingdom levels in the skin microbiome, and especially, we confirmed that different genus or species level microbe was involved in the microbial network according to skin location and Y-, O-group.Figure 5Network analysis of the ASVs on (a) cheeks and (b) forehead of Korean women. Each node represents the ASV and the size of the node is based on relative abundance of each ASV. Color markings indicate the major taxa except for unidentified bacteria or fungi. Shapes represent the level of kingdom, Bacteria (bold) and Fungi (dotted line). The ASVs were selected for bacterial ASVs found in more than half of all samples on the cheeks and forehead, respectively, and for the fungal ASVs with a relative abundance of more than 0.1% in each of the cheeks and forehead samples. The D value is network density calculated using the ratio of the number of edges.Full size image More

Analytical targetsTwo species of undulation motion rays with different pectoral fin shapes bred in KAIYUKAN were analyzed: sharpnose stingray Dasyatis acutirostra and pitted stingray Dasyatis matsubarai (Fig. 1a,b). Blender 2.7925 was used to construct stingray models from pictures26,27 as accurately as possible; Blender is a free and open-source 3D creation suite used to make realistic characters for movies, etc. Detailed information on how to construct models using Blender is provided in our previous paper28. To focus on the effects of pectoral fin movements, we did not consider the body’s shape as in the previous studies12,29. The height and disk width (WD) of all models were set to 0.01 m and 0.44 m, respectively, considering the previous studies30,31. The disk length of each model was determined from WD, referring to the aspect ratio of the rays’ photographs26,27; the disk length (LD) of D. acutirostra and D. matsubarai are 0.348 m and 0.344 m, respectively.Figure 1Analytical targets and description of motion. (a) Analytical model of D. acutirostra. (b) Analytical model of D. matsubarai. (c) Description of motion, (d) the relationship between any two points on the surface before and after the deformation.Full size imageMotionThe motion was given to satisfy the following equations:$$z = left{ {begin{array}{*{20}l} {A;sin left( {omega left( {t – kTleft( {frac{{angl{text{e}}left( {x_{i} ,y_{i} } right) – 10^{{text{o}}} }}{{All;angl{text{e}}}} – theta } right)} right)h_{1} h_{2} } right.} hfill & {left( {10^{{text{o}}} le angl{text{e}}left( {x_{i} ,y_{i} } right) le 170^{{text{o}}} } right)} hfill \ {A;sin left( {omega left( {t – kTleft( {frac{{350^{{text{o}}} – left( {angl{text{e}}left( {x_{i} ,y_{i} } right) – 10^{{text{o}}} } right)}}{{All;angl{text{e}}}}} right)} right)h_{1} h_{2} } right.} hfill & {left( {190^{{text{o}}} le angl{text{e}}left( {x_{i} ,y_{i} } right) le 350^{{text{o}}} } right)} hfill \ end{array} } right.$$
(1)
$$begin{array}{c}{h}_{1}=a{r}_{i}^{3}+b{r}_{i}^{2}+c{r}_{i}end{array}$$
(2)
$$h_{2} = left{ {begin{array}{*{20}l} {dleft( {angleleft( {x_{i} ,y_{i} } right) – 10^{ circ } } right)^{2} + eleft( {angleleft( {x_{i} ,y_{i} } right) – 10^{ circ } } right)} hfill & {left( {10^{ circ } le angleleft( {x_{i} ,y_{i} } right) le 170^{ circ } } right)} hfill \ {dleft( {350^{ circ } – left( {angleleft( {x_{i} ,y_{i} } right) – 10^{ circ } } right)} right)^{2} + eleft( {350^{ circ } – left( {angleleft( {x_{i} ,y_{i} } right) – 10^{ circ } } right)} right)} hfill & {left( {190^{ circ } le angleleft( {x_{i} ,y_{i} } right) le 350^{ circ } } right)} hfill \ end{array} } right.$$
(3)
$$begin{array}{c}{left({r}_{i}-{r}_{i-1}right)}^{2}+{left({z}_{i}-{z}_{i-1}right)}^{2}={left({r}_{i}^{mathrm{^{prime}}}-{r}_{i-1}^{mathrm{^{prime}}}right)}^{2}+{left({z}_{i}^{mathrm{^{prime}}}-{z}_{i-1}^{mathrm{^{prime}}}right)}^{2}end{array}$$
(4)
$$begin{array}{c}angleleft({x}_{i},{y}_{i}right)= angleleft({x}_{i}^{^{prime}},{y}_{i}^{^{prime}}right).end{array}$$
(5)
Equation (1) represents the amount of movement of the model surface in the z-axis direction, where (A) is the amplitude of the pectoral fin tip, (omega) is the angular velocity, (t) is time, (k) is the wavenumber, (T) is the period, angle(({x}_{i},{y}_{i})) is the angle made by the line connecting the center of rotation and any point (({x}_{i},{y}_{i})) on the model surface with the x-axis, Allangle is the range where the motion is given (160°), and (theta) is the phase difference between the movements of the right and left pectoral fins (Fig. 1c). ({h}_{1}) is the weighting from the center to the radial direction: it is necessary to set the amplitude at the ray’s center to zero and increase the amplitude toward the pectoral fin tip (a = 119.786, b = -7.957, c = 0.498). ({h}_{2}) is the weighting in the circumferential direction: it is necessary to increase the amplitude from the anterior to the tip of the pectoral fin and decrease the amplitude from the tip of the pectoral fin to the posterior (d = − 1.563 × 10–4, e = 0.025). Equation (4) is the condition in which the distance between two neighboring points in the same radial direction is equal before and after the movement (Fig. 1d). (r) is the distance between the center of rotation and any point (({x}_{i},{y}_{i})), defined as (sqrt{{x}_{i}^{2}+{y}_{i}^{2}}). Equation (5) defines angle(({x}_{i},{y}_{i})) as being constant before and after the move (Fig. 1c). The variables after the move are marked with ‘. Variables used in the analysis are A = 0.089 m, T = 0.499, k = 1.270, and ω = 12.599 rad/s. Videos of the created motion from the front and the side are shown in the “Supplement” (Supplement Movies 3, 4).Analytical conditionsAnalysis cases were conducted with eight conditions: two types of pectoral fin shape (Fig. 1a,b) and four types of phase difference (0 (T), 0.25 (T), 0.5 (T), and 0.75 (T)). These conditions were set for investigating the effects of phase differences between left and right pectoral fin movements on swimming and how these effects vary with pectoral fin shape.Numerical methodsA CFD simulation of the ray models in the water flow was performed using OPENFOAM, an open-source finite volume method CFD toolbox32, to calculate the forces acting on the rays in each axial direction and the moment around each axis. The governing equations were the continuity equation and the three-dimensional incompressible Reynolds-averaged Navier–Stokes equation, expressed by:$$begin{array}{*{20}c} {nabla cdot u = 0} \ end{array}$$
(6)
$$begin{array}{*{20}c} {frac{partial u}{{partial {text{t}}}} + nabla cdot left( {uu} right) = – nabla p + nabla cdot left( {vnabla u} right) + nabla cdot left[ {nu left{ {left( {nabla u} right)^{T} – frac{1}{3}nabla cdot uI} right}} right], } \ end{array}$$
(7)
where (u) is the velocity vector, t is the time, p is the static pressure divided by the reference density, (nu) is the kinematic viscosity, and I is the unit tensor. The Reynolds number was defined regarding the previous studies3 as:$$begin{array}{c}{R}_{e}=frac{U{L}_{D}}{nu },end{array}$$
(8)
where (U) (/ms) is the given flow speed3 (1.5 × LD/ms), ({L}_{D}) (m) is the length of the ray models, and (nu) is the kinematic viscosity of water at 20 °C (1.0 × 10–6 m2/s). The Reynolds number in this study is 1.8 × 105; considering this, we used the k–ω shear stress turbulence model33,34. The k–ω shear stress turbulence model is a type of Reynolds-averaged Navier–Stokes equation (RANS) turbulence model that is widely used to calculate for the fish swimming flow35,36,37. The overset grid method was used in this study; it is a generic implementation of overset meshes. For both static and dynamic cases, cell-to-cell mapping between multiple, disconnected mesh regions is employed to generate a composite domain38,39. This method permits complex mesh motions and interactions without the penalties associated with deforming meshes. The process is described in detail by Noack40. The calculation volume was 5.4 WD in length, 5.4 WD in height, and 5.4 WD in width (Fig. 2a,b). A hexahedral volume mesh was created using the snappyHexMesh of OPENFOAM. The fluid region was divided into two parts: the overset region and the background region (Fig. 2a,b). The overset region moves and transforms to match the motion of the ray and was made with fine meshes around the analysis target and coarse meshes in the outlying areas; a one-layer boundary layer mesh was created around the analysis target. The overset region shape is an ellipsoid (Fig. 2a,b). The minimum mesh volume is 7.3 × 10–10 (m3), and the maximum mesh volume is 2.6 × 10–2 (m3). The total number of meshes was 9.0 × 105. At the outlet boundary, the average static relative pressure was set to 0 Pa. The surfaces of the fish model were formed into non-slip surfaces.Figure 2Meshes for CFD simulation and differences in force between different meshes. (a) Meshes at the coronal plane of the whole fluid region. (b) Frontal cross-section of the fluid region at the green line in (a). The red region is the overset region. (c,d) Comparison of the instantaneous drag coefficient and the moment coefficient around the y-axis of D. matsubarai between the coarse, fine, and dense mesh.Full size imageThe drag coefficient ({C}_{D}left(tright)), the lateral force coefficient ({C}_{l}left(tright)), the lift coefficient ({C}_{L}left(tright)), the moment coefficient around the x-axis ({C}_{mx}left(tright)), the moment coefficient around the y-axis ({C}_{my}left(tright)) and the moment coefficient around the z-axis ({C}_{mz}left(tright)) were calculated as:$$begin{array}{c}{C}_{D}left(tright)=frac{Dleft(tright)}{frac{1}{2}rho {U}^{2}{L}_{D}{W}_{D}}end{array}$$
(9)
$$begin{array}{c}{C}_{l}left(tright)=frac{lleft(tright)}{frac{1}{2}rho {U}^{2}{L}_{D}{W}_{D}}end{array}$$
(10)
$$begin{array}{c}{C}_{L}left(tright)=frac{Lleft(tright)}{frac{1}{2}rho {U}^{2}{L}_{D}{W}_{D}}end{array}$$
(11)
$$begin{array}{c}{C}_{mx}left(tright)=frac{{M}_{psi }left(tright)}{frac{1}{2}rho {U}^{2}{L}_{D}^{2}{W}_{D}}end{array}$$
(12)
$$begin{array}{c}{C}_{my}left(tright)=frac{{M}_{phi }left(tright)}{frac{1}{2}rho {U}^{2}{L}_{D}^{2}{W}_{D}}end{array}$$
(13)
$$begin{array}{c}{c}_{mz}left(tright)=frac{{M}_{theta }left(tright)}{frac{1}{2}rho {U}^{2}{L}_{D}^{2}{W}_{D}},end{array}$$
(14)
where (Dleft(tright)) is the calculated drag, (lleft(tright)) is the calculated lateral force, (Lleft(tright)) is the calculated lift, ({M}_{psi }left(tright)) is the calculated moment around the x-axis, ({M}_{phi }left(tright)) is the calculated moment around the y-axis, ({M}_{theta }left(tright)) is the calculated moment around the z-axis, and (rho) (kg/m3) is the density of water at 20 °C (998 kg/m3). As shown in a previous study41. the propulsive efficiency (eta) is defined as the ratio of output power ({P}_{o}) to input power ({P}_{e}) which can be written as:$$begin{array}{c}{P}_{o}left(tright)=frac{1}{T}{int }_{0}^{T}Dleft(tright)Udtend{array}$$
(15)
$$begin{array}{c}{P}_{e}left(tright)=frac{1}{T}{int }_{0}^{T}left[Dleft(tright)dot{x}left(tright)+lleft(tright)dot{y}left(tright)+Lleft(tright)dot{z}left(tright)right]dtend{array}$$
(16)
$$begin{array}{c}eta =frac{{P}_{o}}{{P}_{e}}.end{array}$$
(17)
An in-house program calculated the forces acting on rays in each axial direction and the moment around each axis. The numerical method’s validity and reliability were verified by comparing previous experimental and numerical analytical studies of heaving and pitching on airfoil naca001341. A high degree of similarity to previous studies was confirmed; the mean difference in the propulsive efficiency from the previous study of analysis was 5%, and the difference from the previous study of the experiment was 9%. Detailed information such as mesh, length, and velocity, of this analysis method’s verification is provided in the “Supplement”.A grid sensitivity study was conducted using three meshes: coarse, fine, and dense. The coarse mesh has 8.1 × 105 elements, the fine mesh has 9.0 × 105 elements, and the dense mesh has 9.9 × 105 elements. The analysis was conducted using a condition with no phase difference of D. matsubarai. As shown in Fig. 2c,d, the drag coefficient and the moment coefficient around the y-axis are almost the same when the mesh is fine and when the mesh is dense. The mean drag and propulsive efficiency error of fine and coarse meshes are 2.7% and 3.5%, respectively. The fine mesh was used in all simulation cases considering accuracy. We used the same meshes for all cases. More

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Let (y_{itk}) denote the WCR count observed for trap i in week t in year k, and assume it to follow a Poisson distribution with parameter (mu _{itk})$$begin{aligned} y_{itk} | mu _{itk}, sim Poisson(mu _{itk}) end{aligned}$$
(1)
The intensity parameter (mu _{itk}) represents the rate of emergence for a given time period. Instead of allowing it to depend purely on time t, a phenological variable of growing degree days (GDD) is used, as warmer temperatures are required for WCR development25,26,27,28. GDDs reflect the heat accumulation and are defined as an integral of warmth above a base temperature after a given start date:$$begin{aligned} GDD = int (T(t)-T_{base})dt. end{aligned}$$
(2)
The above integral can be approximated by$$begin{aligned} GDD = max left( frac{T_{max} – T_{min}}{2} – T_{base}, 0 right) . end{aligned}$$
(3)
Here (T_{min}) is the minimum daily temperature, (T_{max}) is the maximum daily temperature, and (T_{base}) is a set base temperature. In this study, the base temperature was set to (10,^{circ })C, and the starting date was the beginning of April, which marks the start of the growing season in Austria.The rate of cumulative emergence of the WCR beetle can be described by a Gompertz function. The Gompertz function is a sigmoidal function which describes growth as being slowest at the beginning and the end of a given period and is defined as$$begin{aligned} f(z_t) = alpha exp (-beta exp (-gamma z_t)). end{aligned}$$
(4)
where (alpha) is the upper asymptote, (beta) is a relative starting value, (gamma) is a growth rate coefficient which affects the slope, and (z_t) are the cumulative growing degree days. In this study, one can consider the asymptote as proxy to the saturation level of WCR population growth. Lower values of (beta) suggest an earlier first emergence in the season, while lower values of (gamma) indicate a longer emergence period. To investigate whether there is an association between climate variables and the emergence dynamics, the Gompertz curve parameters were assumed to linearly depend on climate covariates. In this regression modelling framework, a spatially correlated residual structure can be added in either (alpha), (beta), and/or (gamma) if there is evidence to do so.To reflect the nature of the emergence dynamics and to preserve the shape of the increasing Gompertz curve, the parameters of the model were restricted to positive values such that (alpha >0), (beta >0), and (gamma >0). The time at inflection or period of highest growth can be obtained by solving Eq. (4) for the value of t at which the concavity of the function changes. The time at inflection is described as:$$begin{aligned} T_z^* = frac{log (beta )}{gamma } end{aligned}$$
(5)
The Gompertz function describes cumulative emergence. Thus to describe the marginal emergence rate, the derivative of the Gompertz function can be used instead. Consequently, as the WCR trapping data consisted of weekly counts, the rate of emergence (mu _{itk}) is better described by the log of the derivative of the Gompertz function$$begin{aligned} log (mu _{itk}) = log (alpha _{ik}) + log (gamma _{ik}) + log (beta _{ik}) + gamma _i z_{itk} – beta _{ik} exp (-gamma z_{itk}). end{aligned}$$
(6)
The parameters (alpha _{ik}), (beta _{ik}) and (gamma _{ik}) are site and year specific such that:$$begin{aligned}&alpha _{ik} sim N(mu _{alpha _{ik}}, tau _{alpha }) end{aligned}$$
(7)
$$begin{aligned}&gamma _{ik} sim N(mu _{gamma _{ik}}, tau _{gamma }) end{aligned}$$
(8)
$$begin{aligned}&beta _{ik} sim N(mu _{beta _{ik}}, tau _{beta }). end{aligned}$$
(9)
Here, (tau _{alpha }), (tau _{beta }), and (tau _{gamma }) are the precision (inverse variance) parameters of the prior distributions for (alpha), (beta) and (gamma) respectively. Moreover, the means of the distributions (mu _{alpha _{ik}}), (mu _{beta _{ik}}), and (mu _{gamma _{ik}}) can be expressed as functions of known covariates:$$begin{aligned} mu _{alpha _{ik}}= & {} a_{0} + {mathbf {w}}^T X_{alpha _{ik}}, end{aligned}$$
(10)
$$begin{aligned} mu _{beta _{ik}}= & {} b_{0}, end{aligned}$$
(11)
$$begin{aligned} mu _{gamma _{ik}}= & {} g_{0} + {mathbf {u}}^T X_{gamma _{ik}}. end{aligned}$$
(12)
Here (a_{0}) is the intercept, ({mathbf {w}}) is a vector of the regression coefficients, and (X_{alpha _{ik}}) are the location and year specific covariates. The predictors used in the regression of (mu _{alpha _{ik}}) are the average winter temperature, the precipitation sum during winter, the year, the percentage of the agricultural area per Austrian municipality used for cultivating maize crops (maize), and the corresponding centred coordinates of the trap locations; x, y, and their functions (x^2), (y^2), and xy. The parameter (g_{0}) is the intercept for the regression of (mu _{gamma _{ik}}), and u is the corresponding regression coefficient. The predictor used for (mu _{gamma _ik}) is the average yearly spring temperature.The intercepts and regression coefficients ((mathbf {w}) and (mathbf {u})) were given non-informative normal priors N(0, 0.01). The precision parameters (tau _{alpha }), (tau _{beta }) and (tau _{gamma }) were assigned prior distributions Gamma(0.01, 0.01).The model was fitted using WinBUGS through the R2WinBUGS package in R29,30,31. The model was run for 20000 iterations, with a burn-in of 10000 iterations, and a thinning rate of five. Convergence was determined by visual assessments of trace plots and marginal posterior densities. More

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Settlement stage fishesSpecimen collectionData for settlement stage tropical larval fishes includes 1372 swimming speed measurements, collected from >75 unique taxa across 35 families of fishes, most of which are coral reef associated as adults. The data are collected from five locations, including: South Caicos Island (Turks and Caicos Islands, Caribbean – TCI), Green Island or Magnetic Island (exact location not recorded for individual samples, Great Barrier Reef, Australia GI/MI), Lizard Island (Great Barrier Reef, Australia – LI), Calabash Caye (Turneffe Islands Atoll, Belize – BLZ), and Moorea, Society Islands (MOR) (Table 1).Table 1 Sampling locations for settlement stage Ucrit data. Included are the Region, year of collection, location and associated name, as well as the total number of recorded measurements (count).Full size tableData from LI and TCI were obtained almost exclusively from specimens collected using light traps, placed 100–500 m meters off the leeward side of the Island, near either the School for Field Studies facilities (TCI) or the Lizard Island Research Station (LI). An additional eight specimens of newly hatched Acanthochromis polyacanthus, a pomacentrid species which does not have a pelagic phase, were captured with nets on the Lizard Island reefs. Data from GI/MI were obtained using a combination of light traps, beach seines, fence and dip nets.For data collected in Moorea (Mor), specimens arriving over night from the open ocean and attempting to settle on the reef were captured in nets placed on the reef crest. In Belize (BLZ) specimens were collected using a variety of techniques including crest nets, channel nets, light traps and night-light lift nets, although most individuals were collected using light traps and crest nets. Crest net locations were those reported in29. Unless stated otherwise in the “notes” field of the “ucrit_sett_dat” data table (see Online-only Table 1), all U-crit measurements on individuals captured by light traps or crest nets were made on the morning of capture, usually within 6 or 12 hours (please refer to the original publications for methodological details). In a few cases, some individuals were kept in the laboratory for up to 2 days to study changes in swimming speed associated with settlement (see24,30), and here the post-settlement status of the larvae was recorded in the field “stage” in the “fish_id_dat” data table (see Online-only Table 1). Some specimens of the pomacentrid, Abudefduf saxatilis were collected with hand nets from a fish attracting device deployed over a seagrass bed from a dock and are best considered as early post-settlement individuals, although the time since settlement is unknown. All specimens of the labrid, Clepticus parrae were collected with hand-nets from deep fore-reefs. Although they had settled to the fore-reef an unknown period of time before capture, these individuals had yet to undergo complete metamorphosis. Data from such post-settlement individuals should be used with caution, as it is known that swimming performance in some species decreases markedly upon settlement11,24.Most data were collected during the summer months (May through September for TCI and BLZ, November through February for LI), but in MOR, the data came from winter (August). In Belize, data were collected in 2003, 2004 and 2005, totalling 401 U-crit measurements. Data from TCI were collected in 2003, from 109 individuals. Data from LI represented just over half of the settlement stage swimming data (556 measurements), and were collected in 2001, 2002, 2003, 2004 and 2005. A total of 144 measurement were available from GI/MI and were collected in 1992. The 152 U-crit measurements from MOR were from 2010.Captured settlement stage larvae/pelagic juveniles were held in fresh seawater for a minimum of 1–2 hours to reduce stress prior to swimming trials, either with an aeration stone in 24 L buckets (BLZ), or in flow-through seawater aquarium facilities at the Lizard Island Research Station (LI) and the Department of Environment and Coastal Resources at South Caicos (TCI).U-crit protocolAll swimming experiments were conducted at ambient seawater temperatures, which ranged between 25 °C and 30 °C, depending on location and date.Settlement-stage individuals were swum using one of several swimming flumes, including a single-lane swimming chamber11,22, a six-lane swimming chamber12 (see Fig. 1), or a three-lane swimming chamber modified from the design of12. All swimming chambers were constructed from transparent Plexiglass (internal dimensions of swimming area: 185 mm × 50 mm × 50 mm). A removable lid, sealed with an O-ring was used to introduce fish to, and remove them from the chambers. One section of flow straighteners, 45-mm long, was placed just after the inflow in order to reduce turbulence within the chamber. Fish were retained within the swimming area by two 4.0 mm mesh metal retaining fences, which were covered with a finer mesh when required for very small larvae.Fig. 1Design of the swimming channel used for settlement stage larvae, pelagic juveniles and settled juveniles. Shown are Side view (a) & Top view (b, modified from12). This swimming channel can be operated at up to 50 cm s−1. Smaller designs with three channels, or only 1 channel that could obtain higher speeds were used for swimming faster individuals. For data collected by Leis and colleagues, higher speeds were obtained by blocking some lanes using Perspex.Full size imageFlow was generated using a 2.4 Kw swimming pool pump (although the size of the pump varied across the studies), or plumbed into a laboratory seawater system. The speed was set using a protractor mounted on a gate valve and calibrated using the procedures described under the technical validation section below. Faster speeds were also calibrated using an inline blue-white F-300 series flow meter. Flumes were plumbed using union valves so they could be dismantled and easily relocated and installed in field locations. Because the pumps used to run the flumes can heat the water temperature over time, they were plumbed with a minimum reservoir volume of 70 L, with a constant flow through of fresh seawater. A mercury thermometer located in the reservoir was used to ensure temperature remained ambient during the swimming trials. Example field deployments of the swimming channels at various locations can be seen in Fig. 2.Fig. 2Examples of the ‘fast’ swimming flume setup at various field locations. Shown are the Lizard Island Research Station (Great Barrier Reef, Australia, a), the Department of Environment and Coastal Resources aquarium facilities at South Caicos (Turks and Caicos Islands, b), and the dock at the University of Belize Institute of Marine Field Studies at Calabash Caye (Belize, c).Full size imageU-crit was measured by placing specimens in the swimming flume and incrementally increasing water speed until the individual could no longer maintain position for the full-time increment interval. The exact experimental protocols differed slightly among the studies. For fish measured at Lizard Island in November 2000–January 2001, November–December 2001 and South Caicos Island, and most fish at Calabash Caye, the experimental protocol followed7, with speed increments equivalent to approximately three total standard body lengths per second (bls−1) with a time interval of 2 min. This protocol was adopted because settlement stage larvae can vary substantially in size and subsequently their swimming capacity, as swimming speeds are strongly controlled by body size4. Aligning the speed increments with the approximate size category of fishes ensured that the overall duration of the U-crit experiment was relatively similar. For fish measured at Lizard Island during December 2003, speed increments used were 1.6 cm s−1 with a time interval of 5 min. At Lizard Island in 2005, specimens of Amblyglyphidon curacao were subjected to speed increments of 4.2 cm s−1 at intervals of 5 minutes. In Moorea in 2010, all individuals were subjected to speed increments of 6.1 cm s−1 at intervals of 2 minutes. For fish measured at Green Island and Magnetic Island speed increments used were 5 cm s−1 with a time interval of 5 min. At Calabash Caye an experiment was conducted to examine the impact of time increments on U-crit measurements, and the experimental protocol was recorded in this instance.U-crit swimming speed was calculated following17:$$U mbox{-} crit=U+left(t/ti,ast ,Uiright)$$
(1)
Where:U = penultimate speed (speed increment for which the fish swam for the entire duration of the set time interval). Ui = the velocity increment (varied by the specific study).t = the time swum in the final velocity incrementti = the set time interval for each velocity increment (varied by the specific study).While the speed increments used varied across studies in this collated dataset, previous studies have found no effect of varying the length of the time interval (ti) in terms of the resulting swimming speed between fish swum at two minute intervals and those swum at 15 minute intervals for six reef fish species10.Sample handling and morphological measurementsAfter each trial specimens were anaesthetised in chilled water or using clove oil (depending on the location and according to the relevant ethics approvals) and some were photographed while still fresh to maintain body flexibility and to avoid issues with shrinkage due to dehydration associated with preserved samples. Following photographing, the samples were preserved in either 70% ethanol, 95% ethanol, or 10% buffered formalin.From digital images the ImageTool (UTHSCSA 2002) software was used for image analysis. Measurements made from digital images (where available) are shown in Fig. 3, and included: total length (from the outer edge of the caudal fin to the tip of the upper jaw), caudal fin length (from the tip of the caudal fin to the caudal peduncle), body depth (the vertical height of the fish measured at the deepest region), body area (the area of the fish in lateral view excluding the fins but including the head and gut region), propulsive area (the area of the fish including the fins but excluding the head and gut region), muscle area (the area of the fish excluding the fins and the head and gut region), caudal fin depth, caudal peduncle depth and caudal fin area. All measurements were taken to the nearest 0.1 mm. Body width (at the widest region, usually the head) was also measured to the nearest 0.1 mm using vernier callipers. In some cases total lengths (TL) were measured pre-trial using callipers (BLZ, 2003 and 2004). Body length (BL, which is equivalent to SL for postflexion stages) was measured using an ocular micrometer on a dissecting microscope in some studies23.Fig. 3Morphological measurements of settlement stage fishes. Measurements include: total length (TL; outer edge of the caudal fin to the tip of the upper jaw), caudal fin length (CFL; tip of the caudal fin to the caudal peduncle), body depth (BD; height at the deepest region), body area (BA; area in lateral view excluding the fins), propulsive area (PA; area including the fins (naturally fully extended) but excluding the head and gut region where they are inflexible or lack overlaying muscle and cannot be used for propulsion), muscle area (MA; area excluding the fins and the head and gut region), caudal fin depth (CFD; widest section when fully extended), caudal peduncle depth (CPD; height at the narrowest point between the caudal fin and the fish’s body) and caudal fin area (CFA; area with the caudal fins naturally fully extended). Callipers were used to measure head width. Adapted from8.Full size imageLarval development dataset (Australia)Rearing protocolData gathered using a combination of the ‘fast’ and ‘slow’ swimming chambers (see below) on swimming abilities throughout development are available for six species, including two damselfish – Pomacentrus amboinensis and Pomacentrus mollucensis (Pomacentridae; Pomacentrinae); two cardinalfish – Ostorhinchus (Apogon) compressus and Sphaeramia nematoptera (Apogonidae); and two anemone fish – Amphiprion percula and Amphiprion melanopus (Pomacentridae; Amphiprioninae). Note that the pomacentrids have demersal eggs, whereas the apogonids orally brood their eggs.Australian specimens for assessing swimming speeds throughout larval development were obtained mostly from larvae reared at the James Cook University Aquarium facility, from adult broodstock collected from the northern Great Barrier Reef. Adult brood stock were kept in outside aquaria ranging in size from 1000 to 3000 L. The temperature of aquaria was kept between 27 and 29.5 °C, with larvae reared in the Autumn and Winter of 1998. Brood stock were fed a diet of chopped pilchards, prawns and Ascetes twice per day. Eggs were obtained from spawning broodstock before dark on the night of hatching and transferred to a rearing tank. Once hatched, larvae were reared and maintained in 200 L (120 × 60 × 30 cm) black painted glass aquaria that were illuminated by four “daylight” fluorescent tubes. The larvae were maintained in a 14:10 light/dark photo-period at 27.5–29 °C. Cultures of the algae Nannochloropsis sp. were used to green the water during the day. This kept light at the right intensity to prevent “bashing” behaviour (young larvae have a tendency to continually butt their heads against surfaces if the water is clear and the light intensity is too bright). Larvae were fed a diet of >52 micron sieved wild caught plankton, which was occasionally supplemented by rotifers and Artemia spp. when necessary. Larvae were fed twice per day to maintain prey densities of between 2–6 individuals per ml. Examples of ontogenetic series obtained through these rearing methods, and showing pre- and post- flexions stages are show in Fig. 4.Fig. 4Examples of larval developmental series obtained for larvae reared at the James Cook University Aquarium facility. Showin are Amphiprion melanopus (a) and Sphariamia nemaptopera (b).Full size imageU-crit protocolSwimming experiments for older [i.e., postflexion] larvae (see Fig. 4(a)ii–iv and Fig. 4(b)iv–vii) were carried out using the flumes described above for settlement stage fishes. However, these flumes were unsuitable for measurement of swimming capabilities of the delicate younger [i.e., preflexion] larvae (see Fig. 4(a)i and Fig. 4(b)ii,iii). Several characteristics had to be addressed in order to design equipment suitable for the measurement of the swimming capabilities of very young larvae. These included:

The apparatus needed to produce slow flow rates while maintaining laminar flow and minimal boundary layer effects. This is because newly hatched larvae are small enough to effectively utilise the boundary layer, which is broader for slower moving water.

The apparatus had to provide an environment suitable for very young larvae as the trauma of transferring larvae between containers can be fatal. Accordingly, stress associated with sudden changes in light intensity or water quality was minimised by “greening” the water with algae and the use of dark or clear surfaces to avoid “bashing” behaviour. In addition, the apparatus had to be set up within the immediate vicinity of the rearing tanks (or possibly in a rearing tank) to minimise the distance larvae had to be moved.

Two swimming channels were designed and used for younger larvae that were able to meet these requirements. These were designed to operate at “slow” and “medium” speeds. Both channels were able to produce laminar flow at much slower speeds. They consisted of a much wider swimming area so that most of the water flow occurred away from the sides, maximising the area of water not influenced by boundary layer effects. Both were able to be placed in a rearing aquarium of “greened” water. This prevented the larvae from exhibiting “bashing” behaviour, minimised the distance that larvae had to be transferred and meant that there was no change in water quality between the experimental apparatus and rearing tanks (Fig. 5).Fig. 5Design of swimming channels for younger larvae. Shown are side view (a) & Btop view (b). Dimensions are for the “slow” and “medium” flumes respectively.Full size imageFish were retained by a 0.3 mm mesh at the end of the swimming channel for the “slow” chamber and a 1 mm mesh for the “medium” chamber. The “slow” channel was powered by an Eheim 2,000 L per hour pump and the “medium” channel was powered by two such Eheim pumps. The speed for both channels was set using a protractor mounted on a gate valve as for the “fast” swimming chamber used for older larvae, and calibrated according to the description below under technical validation.Each clutch of eggs from each species was raised from hatching through to settlement and experiments were performed periodically throughout this larval period, with sampling days depending on the species. The first swimming trial was conducted on day 1, approximately 12 hours after hatching. Three clutches of each species were used for each swimming trial for the species Pomacentrus amboinensis, Sphaeramia nematoptera and Amphiprion melanopus to ensure that any clutch effects were considered4. While multiple broodstock were available for each species, no record was made at the time from which broodstock the replicate clutches were obtained. For other species only a single clutch was available. In some cases these data included light trap caught specimens to supplement the latest settlement stage. At each experimental age for each clutch 8–12 fish were used in the swimming trials.Larvae were subjected to incremental increases in flow rates equivalent to approximately 3 body lengths (BL) every two minutes until they could no longer maintain position, as for the experimental protocol described above for settlement stage fishes and U-crit calculated as per Eq. 1. Aligning the speed increments with the approximate size category of fishes ensured that the overall duration of the U-crit experiment was relatively similar throughout ontogeny.Sample handling and morphological measurementsFish that were swum, or siblings from the same batch at the same age, were anaesthetised in chilled water then fixed in 10% buffered formalin. After 12–48 hours, larvae were transferred to 70% alcohol and stored. Morphological measurements were carried out by capturing the image of each fish using a stereo dissecting microscope linked to a video recorder. These images were then saved as files on computer. As for settlement stage larvae, the image analysis program ImageTool was then used to measure lengths and areas for different regions of the fish.Measurements were made of total length (from the tip of the caudal fin to the tip of the upper jaw), body depth (the height of the fish measured at the deepest region), body area (the entire area of the fish excluding the fins) and total propulsive area (the area of the fish including the fins but excluding the head and gut region). The regions measured for both pre-flexion and post flexion larvae can be seen in Fig. 6.Fig. 6Measurements made on developmental series larvae. This includes post-flexion larvae which have developed a true caudal fin supported by a hypural plate and discrete soft rays) (a); and pre-flexion larvae that had no hypural plate or soft rays, but a continuous rayless fin-fold from anus to nape (b).Full size imageLarval development dataset (Taiwan and France)Data on development of swimming in larvae of ten species of pelagic-spawning tropical species of commercially important fishes reared by aquaculturists in Taiwan6,27,28 and two tropical species that brood their eggs that were reared for the aquarium trade in France are included26,28 (see Table 2). In addition, very limited, previously unpublished data on larvae of three species of pelagic spawning, commercial species reared in Taiwan are included. The emphasis in these studies was on postflexion-stage larvae, but for some species, swimming data on preflexion and flexion-stage larvae are included. The ‘standard’ six-lane swimming chamber was used for these measurements of U-crit. For larger larvae of some species, half of the lanes were closed off to achieve the faster speeds that these larvae can achieve. Despite this adjustment, some individuals were able to swim faster than the fastest speeds the swim chamber could achieve. In these cases, the speeds are reported in the database as greater than the maximum chamber speed.Table 2 Species whose U-crit swimming ontogeny were studied using reared larvae in Taiwan and France. Included are the location, family, species, the number of specimens assayed (N), the size range of the specimens, and the associated publication of the original data (where available).Full size tableIn Taiwan, larvae were obtained from commercial aquaculture farms (~22.4°N, 120.6°E) SE of Kaohsiung, southern Taiwan, in May 2004 and in May and June 2005. Rearing conditions varied with species, but most were reared in outdoor concrete or earth ponds. Exceptions were Epinephelus spp., which were reared in indoor concrete tanks, and Chanos chanos and some Eleutheronema tetradactylum, which were reared in outdoor concrete tanks under shade cloth. In most cases, the larvae were provided with a “natural” food source (phytoplankton and zooplankton that were resident in the pond). The aquaculturists did not maintain breeding stock, but obtained the pelagic eggs for rearing from elsewhere. The larvae obtained from the aquaculturists were placed in oxygenated plastic bags placed in insulated boxes and transported about 1 h by road to the National Museum of Marine Biology and Aquarium (NMMBA), Kenting, Taiwan (~22.1°N, 120.7°E). In the laboratory the larvae were acclimated in 40 l aquaria filled from the NMMBA seawater system. Each aquarium was fitted with an aerator and kept at ca. 25 °C. The larvae were fed twice daily with live, newly hatched brine shrimp (Artemia nauplii) and 50% of the total volume of water was exchanged with fresh seawater. The aquaria were cleaned daily by suctioning debris off the bottom. The species studied in Taiwan were all native to the western central Pacific, but the original brood stock may not have been obtained locally. The U-crit measurements were made in a shaded outdoor area where large tanks were located to hold adult fishes intended for either research purposes or for addition to the large public aquarium that forms part of the NMMBA campus. The extensive seawater system of NMMBA was used to supply seawater directly into the swimming chamber on a flow through basis. In some cases, this resulted in fluctuations in the calibration of the swimming chamber, which, as a result was calibrated more frequently than was normally the case. Water temperature in the chamber was recorded for each run, and all were within the range of temperatures in the nearby ocean, or in a few cases, the aquaculture ponds from which the larvae were obtained. The swimming chamber time increment interval was five minutes, with an increase in speed at each increment that varied with the flow from the seawater system and the number of lanes open in the swimming chamber, ranging from 1.6 to 5.3 cm s−1.The larvae studied at Lautan Production, a small company located in Meze, France (42.4°N, 3.6°E) in September 2010 were of two species reared for the aquarium trade. Gramma loreto is native to the western tropical Atlantic, and the brood stock came from Cuba. Pseudochromis fridmani is found only in the Red Sea, but the origin of the brood stock is otherwise unknown. Both species produce ‘egg balls’ that are laid in crevices or small caves and tended by an adult until hatching. The eggs typically hatch at night with little remaining yolk and with no fin-ray development, but with mouth open and eyes pigmented. Recently hatched larvae were removed from the spawning tank to rearing tanks with constant illumination and ‘green water’ at a temperature of 26 °C to 28 °C. Cohort date is for the morning when the larvae were removed from the spawning tank. For the first 5 days rotifers were supplied, and from 6 days after hatch (DAH), the larvae were fed with Artemia nauplii all by Lautan employees. Temperatures in the swimming chamber were similar to those in the rearing tank. Larvae of about 5 mm to settlement size (10–12 mm) were used to measure U-crit. The swimming chamber time increment interval was two minutes, with an increase in speed at each increment of 3.2 cm s−1.Larvae from Taiwan were either preserved in 75% ethanol or in some cases in Bouins Solution for future histology research. Larvae from Lautan were preserved in 75% ethanol. Measurements were made within 24–48 hours after preservation. Body length (BL) was measured on all larvae using a dissecting microscope ocular micrometer: this is Notochord Length (tip of snout to tip of notochord) for preflexion and flexion-stage larvae, and Standard Length for postflexion larvae (tip of snout to end of hypural plate). For some larvae from Taiwan additional measurements were made using Scion Image for Windows (Beta 4.02, Scion Corporation, Frederick, MD): Total Length (tip of snout to tip of posterior-most fin), Total Lateral Area (including fins) and Propulsive Area (Fig. 6), the last as defined by4 (see Fig. 6).Ethic declarationsData collated here are from a large array of studies collected across a range of institutions and locations, and to our knowledge in all cases complied with the required ethics procedures at the relevant institution at the time of data collection. Portions of this work were carried out under Australian Museum Animal Care and Ethics Approval 01/01 (JML) and James Cook Ethics Approvals A202, 402 (RF). In France, research was carried out under permits issued by CNRS to the USR 3278 CNRS/EPHE team to conduct research experiments in the field and laboratory at all locations (under the “Hygiène et Sécurité” section). In Moorea, the research was carried out under permits issued by le Délégué Régional à la recherche et à la technologie de la Polynesie française. More

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