The 2015-2016 El Niño increased infection parameters of copepods on Eastern Tropical Pacific dolphinfish populations.

The oceanographic conditions of the Pacific Ocean are largely modified by El Niño (EN), affecting several ecological processes. Parasites and other marine organisms respond to environmental variation, but the influence of the EN cycle on the seasonal variation of parasitic copepods has not been yet evaluated. We analysed the relation between infection parameters (prevalence and mean intensity) of the widespread parasitic copepods Caligus bonito and Charopinopsis quaternia in the dolphinfish Coryphaena hippurus and oceanography during the strong 2015-16 EN. Fish were collected from capture fisheries on the Ecuadorian coast (Tropical Eastern Pacific) over a 2-year period. Variations of sea surface temperature (SST), salinity, chlorophyll a (Chl-a), Oceanic Niño Index (ONI), total host length (TL) and monthly infection parameters of both copepod species were analysed using time series and cross-correlations. We used the generalised additive models for determine the relationship between environmental variables and infection parameters. The total body length of the ovigerous females and the length of the eggs of C. bonito were measured in both periods. Infection parameters of both C. bonito and Ch. quaternia showed seasonal and annual patterns associated with the variation of environmental variables examined (SST, salinity, Chl-a and ONI 1+2). Infection parameters of both copepod species were significantly correlated with ONI 1+2, SST, TL and Chl-a throughout the GAMLSS model, and the explained deviance contribution ranged from 16%-36%. Our results suggest than an anomaly higher than +0.5°C triggers a risen in infection parameters of both parasitic copepods. This risen could be related to increases in egg length, female numbers and the total length of the ovigerous females in EN period. This study provides the first evidence showing that tropical parasitic copepods are sensitive to the influence of EN event, especially from SST variations. The observed behaviour of parasitic copepods likely affects the host populations and structure of the marine ecosystem at different scales.

Introduction

The El Niño-Southern Oscillation (ENSO) creates fluctuations in the sea surface temperature (SST) of the Tropical Eastern Pacific (TEP), and it has been suggested that its frequency and magnitude will increase in the future [1,2]. During El Niño (EN) events, the equatorial surface waters become considerably warmer (+0.5°C), particularly along the western coast of South America [3], which has a profound influence not only on the tropical Pacific, but also on many regions all over the world [4,5,6,7,8].

Parasites of aquatic organisms are sensitive to changes in abiotic factors, such as temperature [9,10,11], precipitation [12,13], salinity [14,15], hurricanes [16], the North Atlantic Oscillation (NAO) [8], EN [6] and ENSO [8]. Several studies have shown that climate change strongly affects performance, population dynamics and distribution of marine organisms [6,17,18,19]. In particular, ENSO affects host-pathogen relationships of some marine organisms by reducing host immunity and increasing pathogen virulence [8,16,19,20,21,22]. However, most of these studies have been carried out on fungal, viral, protozoan [8,22,23,24,25] or internal metazoan parasites [9,26,27], while ectoparasites, which are more exposed and influenced by environmental variables, remain poorly studied.

One of the most significant oceanographic features of the upper-ocean circulation system off the Ecuadorian coast is the Equatorial Front. This system isolates the cold, nutrient-rich waters of the Humboldt Current moving northwest and the South Equatorial Current from the warmer, nutrient-poor surface waters in the north [28]. This oceanographic pattern changes under the influence of EN and is characterised by unusually warm SSTs in the equatorial Pacific [3]. Along the coast of South America, EN weakens the upwelling of cold, nutrient-rich water, thus affecting the abundance, composition and distribution of phytoplankton, zooplankton and pelagic fish communities [29,30].

Parasitic copepods affect the growth, fecundity and survival of both wild and farmed fish hosts [31,32,33]. These parasites attach to the skin or gills of their hosts to feed on their mucus, tissues or blood and leave open wounds that can result in secondary infections, leading to increased mortality at high infection levels [33,34]. Two of the parasitic copepods infecting the dolphinfish Coryphaena hippurus Linnaeus, 1758 in the Atlantic Ocean and the Mediterranean Sea are Caligus bonito Wilson, 1905 and Charopinopsis quaternia Wilson, 1935 [35,36,37]. The dolphinfish is an oceanic epipelagic fish found worldwide in tropical and subtropical waters, where it is sought after by commercial and recreational fishers [38]. Caligus bonito, a species of the family Caligidae, has also been reported on several other fish hosts (i.e., Auxis rochei (Risso, 1810), Katsuwonus pelamis (Linnaeus, 1758), M. curema Valenciennes, 1836, Mugil liza Günther, 1880 reported as M. platanus, among others) [39,40], while Ch. quaternia, a species of the family Lernaeopodidae, is a little known species, reported mainly from dolphinfish [35]. Members of the family Caligidae are responsible for most of the documented disease outbreaks in cultured marine species [32]. Parasitism in mariculture and wild populations could be better managed by knowing the responses of the parasitic copepods to environmental changes in the eastern tropical Pacific Ocean.

In this context, the goal of this study was to determine the correlation between the infection parameters of C. bonito and Ch. quaternia in the dolphinfish C. hippurus during the non-EN and EN periods of two consecutive years (2015 and 2016).

Materials and methods

Collection of fish hosts

Fish were collected from the fishing port “Playita Mía” Beach (00°57′0.92″S; 80°42′29.47″W), in the city of Manta, Manabí, Ecuador. This port holds the most extensive records of dolphinfish landings for the period 2008–2012, among all Ecuadorian fishing ports [28] (Subsecretaría de Recursos Pesqueros, Viceministerio de Acuacultura y Pesca, unpubl. data). Ecuador has two distinct seasons: the wet/warm (rainy) season from December to April and the dry/cold (dry) season from June to November [41], with the air temperature ranging from 26°C during the dry season to 31°C during rainy season [42].

The Ecuadorian artisanal fishing fleet for large pelagic species is divided into the inshore and the oceanic fleet, depending on the operational distance from the coast [28]. The inshore fleet is formed by small-size fibreglass boats fishing for 2–3 days in “inshore” waters, 40–200 nautical miles (M) from the coastline, while the oceanic fleet consists of medium to large size “mother-ship” boats, fishing for up to 25 days and reaching the 100°W longitude beyond the Galapagos Archipelago and as far west as 94°W south of the Peruvian coast [28]. The dolphinfish used in this study were captured by the inshore fleet and were therefore relatively fresh and not excessively manipulated.

The dolphinfish were caught by using long lines over 2 years, in 1-month intervals (December 2013 to November 2015). The non-EN sampling period was from December 2013 to February 2015, whereas the EN period was from March to November 2015. Due to the absence of previous reports on the prevalence of both parasite species from the TEP, we used a preliminary sampling of 154 dolphinfish to establishing baseline prevalence during the non-EN period (81% for C. bonito and 31% for Ch. quaternia). The accepted levels of risk (α = 0.05) and sensitivity of the sampling and identification methods for the parasites were considered. We assumed that such diagnostic methods have a sensitivity of 75% due to human error (through handling and identification). Thus, assuming a Poisson distribution for the probability of identifying C. bonito and Ch. quaternia, the monthly sample size was obtained using the formula n = 4/prev, where n was the fish sample size, 4 originated from–Ln (α*sensitivity of the diagnostic method) and prev was the prevalence of the fish population [43]. The sample size values for C. bonito and Ch. quaternia were 5 and 13 animals, respectively. Thus, the monthly sample size of the two species for this study was 13 specimens.

Parasitological examination

Due to the dynamics of commercial activity in the fishing port, fresh C. hippurus landed by the artisanal fishers were revised in situ while they were eviscerated and sold. For this reason, only the total length (TL) of each fish was recorded, and copepods were collected from both the opercular and buccal cavities, whereas the gills were stored in plastic bags, labelled and transported in ice-coolers to the laboratory for further microscopic examination. The parasites were washed in physiological saline solution (0.9%) and fixed in 96% ethanol. For taxonomic identification, copepods were cleared in increasing concentrations of glycerol/70% ethanol (1:20; 1:10; 1:5; 1:2), mounted on slides, and observed under optical microscopy to identify them using taxonomic keys [44,45].

The total body length of the 290 ovigerous females (OF) and the length of the 20 eggs of C. bonito, collected in both periods, were measured in milimetres with an ocular micrometre under a 10x magnification. Additionally, we calculated the gender proportion in both periods.

Environmental variables

To describe the effects of EN on the prevalence and intensity of C. bonito and Ch. quaternia in dolphinfish, we included the Oceanic Niño Index (ONI) as an environmental variable; it is one of the most commonly used parameters to measure the EN and La Niña events. This index represents the monthly average values of the SST for the months before and after the normal conditions, which are then compared with the normal SST of the current month [46]. The EN variability is obtained from the ONI from the 1+2 region, which is the smallest and eastern most EN regions (0–10°S, 90–80°W) and corresponds to the region of coastal South America. To indicate the EN conditions, the ONI of 3.4 region must be +0.5 °C or higher for at least five consecutive months, indicating that the east-central tropical Pacific is significantly warmer than usual. Values of ONI 1+2 were obtained from the National Weather Service Climate Prediction Center NOAA.

Values of SST, salinity and Chlorophyll a (Chl-a) were obtained through the R statistical package [47], using the ´xtracto 3D´ script [48]. The ´xtracto3D´ tool allows direct access to SST, salinity and Chl-a sensors [49]. The sensors used were the Advanced Very High Resolution Radiometer (AVHRR) for SST, the Hybrid Coordinate Ocean Model (HYCOM) for salinity and the Moderate Resolution Imaging Spectroradiometer (MODIS) for Chl-a. Monthly SST, salinity and Chl-a data were used to calculate values of these variables from the inshore fishing area (2°N;79°W –4°S;79°W and 2°N;83°W–4°S;83°W). Environmental variables were used to explain the variability of prevalence and the intensity of parasitism in the dolphinfish during the EN of 2015 to 2016.

Data analysis

Dolphinfish sizes were grouped into 10 cm TL bins to determine whether the size distribution of the hosts varied between non-EN and EN periods. Differences in host size between non-EN/EN periods and seasons (dry and rainy) were tested with two-way analysis of variance (ANOVA). The prevalence (percent of infected hosts for each parasite species) and the mean intensity (the mean number of a particular parasite species per infected host) were calculated monthly [50].

To determine the relationship between the environmental variables (SST, salinity and Chl-a) and the infection parameters (prevalence and mean intensity) of C. bonito and Ch. quaternia in dolphinfish, we used the generalised additive models for location of scale and shape (GAMLSS) [51]. Additionally, multicollinearity of variables was evaluated through a variance inflation factor index (VIF) for which the usdm package of R was used. To decide which variables were discarded, a threshold of VIF < 4 was established and considered in the GAMLSS analysis [52]. The models were obtained assuming a normal distribution for prevalence and log normal distribution for mean intensity. The Akaike information criterion (AIC) value in the model setting GAMLSS package in R was used to fit the models. The best statistical model was selected by performing a forward procedure using the stepGAIC (generalised Akaike information criterion) function in the GAMLSS package, as this assessed the contribution of each variable and their combinations in the final model through an iterative process. This function chooses the best model based on the lowest AIC value. In addition, the power of the fit of each model was evaluated through the explained deviance (ED), expressed as a percentage [51].

Spectral analyses by Fourier series [53] were used to extract temporal variability patterns and periodical cycles of TL, SST, salinity, Chl-a, and infection parameters of C. bonito and Ch. quaternia in C. hippurus, along with the monthly patterns of ONI 1+2 (Statistica v.6 Statsoft©). This analysis required data points equally spaced in time [12,13,54]. Each temporal data set was transformed into sine curves of the same amplitude or harmonic frequencies [55] and it was represented in a periodogram. The harmonic frequencies, measured as spectral densities (strength of the frequency signal), represented a temporal scale of maximum variability in the temporal distribution [56]. Any marked frequency peaks were interpreted as a temporal scale of maximum variability to show trends of infection parameters and environmental variables. Spectral density values of parasite infection parameters and environmental variables were compared using cross-correlation coefficients. The cross-correlation quantifies the temporal associations between variables and provides a measure of the similarity between two different data sets, determining the extent to which data sets exhibit correlated periodic variations. Time lags refer to the delayed responses of dependent variables; lag 0 corresponds to immediate response [57]. The time lag with the highest correlation coefficient is taken as the accurate time lag between the two-time series [58]. The cross-correlation coefficients were calculated for a significance of p < 0.05 [59]. The differences in the total length of OF, egg length and sexual proportion between non-EN and EN were evaluated with the Kruskal–Wallis test. These analyses were performed in Statistica v.6 Statsoft©. Environmental and biological values were shown as minimal and maximal values (mean ± standard deviation).

Ethics statement

The permit necessary to carry out parasite sampling and collection was obtained from the Ministerio de Ambiente del Ecuador (permit number 011 JMC-DPAM-MAE). The target species is not endangered or protected, and the samples were obtained from the artisanal fishery of dolphinfish. There were no additional ethical considerations linked to this research.

Results

We collected 956 specimens of dolphinfish C. hippurus, 674 in the non-EN period, with TL from 51.4−135 cm (mean 72.88 ± 12.45 SD), and 282 in the EN period, with TL from 50.2−136 cm (74.54 ± 15.64) (Fig 1A). Host size did not significantly differ between non-EN and EN periods (F1, 953 = 2.99; p > 0.05). In non-EN, the mean host size in rainy season (79.47 ± 0.92 cm) was significantly higher than dry season (69.48 ± 0.64 cm); similarly, in EN, the mean host size in rainy season (81.40 ± 1.32) was significantly higher than that in dry season (72.04 ± 0.76) (F3, 951 = 40.06; p < 0.05). A post hoc test showed that host size was not significantly different between the rainy seasons for the non-EN and EN periods, but differed between the dry seasons for the non-EN and EN periods. The size distribution of C. hippurus presented a unimodal distribution with modes of 60–69.9 cm, following the same trend for the non-EN and EN periods (Fig 1B–1C); however, there was a high number of larger dolphinfish (> 80 cm) during the EN period (Fig 1C). The TL fluctuated temporally, with a peak of maximum variability every 11 months (Fig 1D).

Fig 1

The temporal fluctuation of total length for Coryphaena hippurus and size-frequency during non-El Niño (non-EN) and El Niño (EN) periods.

(A) total length (TL) and Oceanic Niño Index (ONI 1+2), size structure (size classes of 10 mm intervals) in (B) non-EN periods and (C) EN periods, (D) spectral density of TL (black line) and ONI 1+2 (dotted line).

Infection parameters of C. bonito and Ch. quaternia were significantly correlated with ONI 1+2, SST, TL and Chl-a throughout the GAMLSS model, and ED contribution ranged from 16–36% (Table 1). Salinity was not a predicting variable for infection parameters of both copepod species.

Table 1

The general additive models (GAMLSS) for the prevalence and mean intensity of Caligus bonito and Charopinopsis quaternia in Coryphaena hippurus.

Model	Df	Global deviance	Percent of explained deviance	Akaike criterion	p
Prev Cb ~ cs(ONI 1+2) + cs(SST) + cs(Chl-a) + cs(TL)	18	162.72	21.9	198.72	p< 0.001
Int Cb ~ cs(ONI 1+2) + cs(Chl-a) +cs(TL)	14	71.65	36.18	99.65	p< 0.001
Prev Cq ~ cs(ONI 1+2) +cs(Chl-a) +cs(SST) + +cs(TL)	18	162.72	16.84	198.72	p< 0.001
Int Cq ~ cs(ONI 1 +2) + cs (SST) + cs (Chl-a) + cs(Lt)	18	101.15	16.28	137.16	p< 0.001

Abbreviations: Prev Cb: prevalence of Caligus bonito; Int Cb: mean intensity of Caligus bonito; Prev Cq: prevalence of Charopinopsis quaternia; Int Cq: mean intensity of Charopinopsis quaternia; ONI 1+2: Oceanic El Niño Index region 1+2; SST: sea surface temperature; Chl-a: chlorophyll-a; TL, total length of Coryphaena hippurus; Df: degrees of freedom; cs: cibic splines.

The SST ranged 21.30–26.95°C (24.16 ± 1.68°C) (Fig 2A), salinity 32.7−34.74 Practical Salinity Units (PSU) (33.58 ± 0.60 PSU; Fig 2B), Chl-a from 0.49−1.37 μg L-1 (0.85 ± 0.25 μg L-1; Fig 2C) and ONI 1+2 from -0.78−2.87 (1.0 ± 1.19; Fig 2A–2C and S1 Appendix). SST was not significantly different between seasons (F1, 20 = 0.58; p > 0.05) in both periods, but it was significantly higher during EN (25.3°C) than non-EN (23.5°C) (F1, 20 = 13.24; p < 0.05). Salinity was not significantly different between seasons (F1, 22 = 0.24; p > 0.05) in both periods, but it was significantly higher during EN (34.1 PSU) than non-EN (33.3 PSU) (F1, 22 = 15.50; p < 0.05). Chl-a was significantly higher in rainy (1.01 μg L-1) than dry season (0.71 μg L-1) (F1, 13 = 9.72; p < 0.05) in non-EN period, but not between seasons (F1, 7 = 4.97; p > 0.05) during EN period.

Fig 2

The temporal fluctuation of environmental variables of the Tropical Eastern Pacific from December 2013 to November 2015.

(A) sea surface temperature (SST) and Oceanic Niño Index (ONI 1+2) fluctuation, (B) salinity and ONI 1+2 fluctuation, (C) chlorophyll-a (Chl-a) and ONI 1+2 fluctuation, (D) the spectral density of SST (black line) and ONI 1+2 (dotted line) by Fourier series (x-axis in months), (E) the spectral density of Chl a (black line) and salinity (dotted line) by Fourier series (x-axes in months).

The SST, Chl-a, salinity and ONI 1+2 fluctuated temporally (Fig 2A–2C), with a peak of maximum variability every 11 months (Fig 2D–2E). Additionally, we found a significant positive cross-correlation between SST, salinity and Chl-a with ONI 1+2 with no lag, thus showing an immediate response of environmental variables resulting from the change in ONI 1+2.

The time series of the infection parameters of C. bonito showed considerable variation over the 2-year period; prevalence fluctuated from 29%-100%, with a mean intensity of 2.4–14.36 (6.73 ± 2.82) individual parasites per fish (Fig 3A and 3B and S2 Appendix). Spectral analysis of prevalence and mean intensity of C. bonito showed peaks of high variability every 11 months (Fig 3C), as observed for SST, Chl-a, salinity and ONI 1+2 (Fig 2D–2E). Positive cross-correlation among prevalence, mean intensity, Chl-a and ONI 1+2 were observed at lag 0. A significant association was revealed between prevalence and mean intensity with SST with no lag (Fig 3D).

Fig 3

The temporal fluctuation (2013–2015) of prevalence and mean intensity of Caligus bonito in Coryphaena hippurus from the Tropical Eastern Pacific.

(A) prevalence and Oceanic Niño Index 1+2 (ONI 1+2), (B) the mean intensity and ONI 1+2, (C) the spectral density of prevalence (black line) and mean intensity (dotted line) by Fourier series, (D) cross-correlations between the prevalence and mean intensity of C. bonito and ONI 1+2.

The infection parameters of Ch. quaternia fluctuated over the 2-year period, with prevalence ranging 14%-65% and mean intensity from 2.33−9.28 (5.5 ± 1.86) (Fig 4A–4B and Table 2). Spectral analysis of these two parameters showed a peak of high variability every 3 and 11 months, respectively (Fig 4C). Cross-correlation analysis showed a significant association of prevalence and mean intensity of Ch. quaternia with ONI 1 + 2, Chl-a and SST with a 4-month lag (Fig 4D). Significant cross-correlation was found between the mean intensity of Ch. quaternia and SST with no lag (Fig 4D).

Fig 4

Temporal fluctuation (2013–2015) of prevalence and mean intensity of Charopinopsis quaternia in Coryphaena hippurus from the Tropical Eastern Pacific.

(A) prevalence and Oceanic Niño Index 1+2 (ONI 1+2), (B) mean intensity and ONI 1+2, (C) the spectral density of prevalence (black line) and mean intensity (dotted line) by Fourier series, (D) cross-correlations between the prevalence and mean intensity of Ch. quaternia with ONI 1+2.

Table 2

Infection parameters of copepod Caligus bonito and Charopinopsis quaternia parasitizing Coryphaena hippurus from the Tropical Eastern Pacific.

In parenthesis number of fish revised.

	Caligus bonito		Charopinopsis quaternia
	Prevalence	Mean intensity	Prevalence	Mean intensity
December 2013 (21)	71	6.46 ± 5.08	14	2.33 ± 2.31
January 2014 (62)	92	6.1 ± 4.14	40	5.76 ± 7.73
February 2014 (71)	73	8.85 ± 4.22	27	4.1 ± 6.61
March 2014 (9)	38	12.5 ± 0.7	-	-
April 2014 (25)	52	4.69 ± 5.92	28	8.28 ± 7.78
May 2014 (60)	60	4.3 ± 6.86	40	5.41 ± 2.87
June 2014 (51)	100	5.86 ± 3.89	20	4.6 ± 6.15
July 2014 (22)	77	4 ± 3.2	27	5.83 ± 10.4
August 2014 (75)	93	6.68 ± 4.89	41	6.55 ± 11.66
September 2014 (68)	85	5.16 ± 5.03	22	5.06 ± 5.99
October 2014 (74)	95	8.08 ± 5.41	28	4.57 ± 7.64
November 2014 (43)	84	8.72 ± 4.93	49	8 ± 12.81
December 2014 (33)	100	7.69 ± 5.02	45	8 ± 8.80
January 2015 (30)	100	11.33 ± 8.34	40	4.41 ± 5.66
February 2015 (29)	90	4.46 ± 2.90	28	14.62 ± 20.80
March 2015 (17)	29	2.4 ± 2.19	41	9.28 ± 12.06
April 2015 (13)	69	3.88 ± 3.05	31	14.75 ± 26.83
May 2015 (17)	71	8.16 ± 6.32	65	3.18 ± 3.4
June 2015 (58)	72	5 ± 3.77	33	4.26 ± 2.64
July 2015 (43)	93	4.75 ± 3.12	44	5.31 ± 7.20
August 2015 (40)	73	5.41 ± 4.06	60	6.71± 7.58
September 2015 (27)	81	14.36 ± 9.88	37	7.4 ± 10.34
October 2015 (30)	87	5.69 ± 3.71	20	5.16 ± 9.72
November 2015 (30)	97	7.97 ± 5.29	17	4.4 ± 5.64

The results of the Kruskal–Wallis tests showed that egg length (KW-H(1, 1214) = 88.16; p < 0.05) and gender proportion (KW-H(1, 83) = 3.76; p < 0.05) were significantly different between non-EN and EN periods. In the latter, eggs were larger, and females more abundant (Fig 5A). The total body length of OF showed no significant differences between non-EN and EN periods (KW-H(1, 292) = 1.05; p > 0.05) (Fig 5B); however, there was a clear tendency to larger females in EN periods.

Fig 5

Egg length and the total length of ovigerous females of Caligus bonito in relation to non-El Niño (non-EN) and El Niño (EN) periods.

(A) egg length, (B) total length of ovigerous females.

Discussion

Changes in the infection parameters of copepods are explained by the variation of those oceanographic (SST, Chl-a and ONI 1+2) and biological variables (TL), associated to EN event. This climatic phenomenon is characterised by warmer values of the equatorial Pacific SST altering both physical and biological oceanography. Evidence has demonstrated that ENSO can modify the infection parameters of parasites in marine organisms; however, these studies have only been carried out in the temperate latitudes [6,17,19,20]. Although our results come from a short time series, they allow detecting periodic changes in oceanographic variables and infection parameters. This is the first tropical survey to provide evidence that increased SST promotes higher infection parameters of two species of parasitic copepods.

The host factor

Host length showed an annual pattern, with larger individuals occurring in the rainy seasons and smaller ones in the dry seasons, which was consistent during the EN and non-EN periods. These peaks might be associated with migration of large and small fish individuals during reproductive periods and/or favourable conditions for prey availability in the area. Seasonal peaks of fish abundance and size, associated with variable SST, have been widely documented in dolphinfish from the Atlantic and Pacific Oceans [60,61,62,63,64,65,66,67,68], which indicates the presence of at least two cohorts across the year associated with pre-spawning migration or favourable conditions, such as thermal fronts [60,62,69]. It has mentioned that the dolphinfish exhibits bimodal reproductive behaviour, thus they apparently have different size groups arriving at different time periods across the year [67,70]. Size distribution was similar between non-EN and EN periods, although a higher number of larger specimens (> 75 cm) appeared during the latter, thus causing a peak in September. The recruitment of larger animals did not change the seasonal pattern during the year in both periods (non-EN and EN), but promoted significant differences between the dry seasons of such periods. The occurrence of larger individuals of C. hippurus could be related to the increase in SST during the EN period, because of the preference of species for the warm water pool. Two of the most important oceanographic variables correlated with the high catching rates in the Atlantic and Pacific Oceans are warm SST and low levels of surface chlorophyll-a concentration [71,72,73]. These conditions coincided with EN periods that favoured the greater landings of dolphinfish during EN events of 1983, 1987 and 1998 [74].

The environmental factors

We quantified an annual pattern of the oceanographic variables (Chl-a, salinity and SST) at roughly 11-month cycles, where the two known climatic seasons; rainy (wet/warm) from December to May and dry (dry/cold) season from June to November were recognized. This time series (24 months) was related to the complex, highly dynamic oceanography of TEP, influenced by the Humboldt Current and Equatorial countercurrent. It is recognized that the oceanic environment in the TEP varies seasonally, inter-annually and on larger time scales (decadal and multi-decadal) [75]; therefore, an extended time series would be required to obtain stronger data comprising a more extensive range of interannual variations. The Humboldt Current is often described as carrying cold, nutrient-rich waters northward, promoting upwelling processes off Ecuador, Peru and northern Chile. This current recedes southwards around December each year resulting from the flow of warm waters of the South Equatorial countercurrent [40,76]. The SST, salinity and Chl-a values were higher during rainy than dry season in both years, but the first variable increased during the dry season of 2015 and showed a positive correlation with ONI 1+2. This pattern was previously observed in TEP, where EN modified the Humboldt Current System, affecting different environmental variables (i.e., Chl-a, salinity and SST), as well as the distribution of Pacific fish and squid [77,78,79,80,81].

Infection parameters annual patterns

The infection parameters of C. bonito and Ch. quaternia showed an annual behaviour on a roughly 11-month cycle. This annual pattern is characterised by lower average values the rainy season than in dry season, which is inverse to the TL pattern of host. Although host size is frequently recognised as a determinant of parasite abundance (as larger hosts may harbour higher numbers of individual parasites than smaller hosts) [82], our findings showed an opposite pattern, as seen in other hosts [83,84,85]. This may be a consequence of at least three factors: (1) host immunity; larger fish have more efficient immune resistance than younger fish as a defence mechanism against external infections [86], thus reducing the chances of parasite infections; (2) two cohorts with variations in their relative abundances of parasitic taxa. Apparently, two cohorts of dolphinfish are present every year in both the Eastern Central Pacific and the Atlantic Ocean [69,87,88], which could reflect variations in infection parameters between size classes or distribution areas, due to their characteristic of segregating by size and sex [88,89,90,91]; and (3) the migration pattern of host can affect parasite dynamics. The dolphinfish is a highly vagile species with migrations conditioned by the SST (20°C) and by its reproduction pattern, voracious appetite and availability of floating objects [38,89]. Thus, habitats with different environmental variables and host diversity and abundance might affect the prevalence and abundance of parasites. These hypotheses could be clarified when the biology of C. hippurus in the Eastern Central Pacific is studied.

The infection parameters of C. bonito and Ch. quaternia were explained by TL, Chl-a, SST and ONI 1+2, indicating that EN had an effect on the infection parameters of both species. The increased SST modified the infection parameters of both copepod species and other environmental variables, mainly in the dry season during EN, thus altering the seasonal cycle (dry-rainy). However, higher prevalence and mean intensity in Ch. quaternia and mean intensity in C. bonito were more evident during EN; whereas prevalence of the latter copepod species raised from May 2014 (non-EN period) when ONI 1+2 was <0.5°C higher than usual. Enhanced prevalence of C. bonito might be due to its preference for warm water that increases its abundance in the tropics [91,92]. Even though from June to November 2014 was a non-EN period, SST was higher than the historical average values (1982–2016) for those months (21.3−24.5°C vs. 20.5−23°C, respectively) [93], thus indicating that the East-central Tropical Pacific was significantly warmer than usual (S2 Appendix). Alterations on abiotic factors can directly influence the infection dynamics of parasites [94], mainly in ectoparasites with direct life cycles (e.g., crustaceans, copepods and monogeneans) and in close contact with the environment [15]. High temperatures are often associated with increased frequency or severity of infection, as a result of altered pathogen development and survival, physiological changes and range expansion of the host [95]. For example, the generation time of sea lice (Caligus rogercresseyi) ranges from 50 days at 12°C to 114 days at 7°C; a shorter generation time has been related to warmer temperatures [96].

The association between the prevalence of Ch. quaternia with SST, TL and Chl-a showed a 4-month lag; in contrast, mean intensity showed an immediate response. An increase in intensity occurred first (January 2015), and several months later (May 2015), when prevalence raised, suggesting that infected fish showed higher infection rates until the parasites began to infect new hosts. Since Ch. quaternia and C. bonito shared the site of infection [97], it is likely that EN triggered an increase in their numbers per infected host, which could compete for space and spread to other hosts after some time. Although copepod abundance depends on their intrinsic fecundity and rates of growth and development, density-dependence intra- and inter-specific competition, as well as host responses to infestation, should also be considered [98].

Copepods as parasites in changing conditions

Higher infection levels could be related to increases in egg length, female numbers and the total length of the OF in EN periods. Most studies on the effect of temperature on the reproductive parameters of copepods have been carried out in temperate species, and very few for tropical groups, like Caligus [98,99]. It is assumed that larger copepod females produce larger eggs, thus increasing survival of nauplii and improving their chances of reaching suitable hosts [100,101]. Another important factor is the increased rate of infecting larval stages of parasitic copepods at higher temperatures [102,103], which causes higher infection rates [101,104,105]. For example, this effect has been documented in the parasitic branchiuran Argulus coregoni Thorell, 1865 infecting Salmo trutta Linnaeus, 1758 populations from Finland [105]. Thus, with generalist parasites such as C. bonito [35], with a greater availability of oceanic hosts and both strong and long-term shifts towards favourable environmental conditions, we expect an increase in the infection parameters of C. bonito. These results contribute to a deeper knowledge of copepods, mainly caligids, in tropical waters. However, further studies assessing the effects of global climate change or oceanographic phenomena (e.g. EN) on the reproductive dynamics of parasitic copepods and their effects on hosts are required.

Parasites and global warming

Future ENSO events will be stronger and more frequent due to currently recognised global warming trends [1]. In recent years, NOAA has registered record SSTs at a global level and predicts that SST will increase throughout the rest of this century [106]. The models proposed by the Intergovernmental Panel on Climate Change (IPCC) predict that SST will be 1.1–2.9 °C higher by 2100, based on the most conservative B1 emission scenario, and by 2.0–5.4 °C higher, based on the more realistic A2 scenario [107,108]. The present study showed the positive relationship between EN in the Ecuadorian Pacific and infection parameters of two species of parasitic copepods. In the context of global climate change, the increase in water temperatures will influence the emergence and re-emergence of diseases, with adverse effects on hosts, modifying their spatial range and seasonal abundance, and causing a rupture in biological interactions. These changes could have significant ecological and economic consequences, especially in relevant fishing resources, such as C. hippurus and other fish species of the Eastern Pacific. Therefore, it is necessary to carry out long-term monitoring of this kind of parasite-host model to extrapolate the effects of environmental shifts on those interactions. We also recommend evaluating the effect of environmental variables on the infection parameters of tropical parasitic copepods under experimental laboratory conditions.

Oceanographic variables from ONI 1+2 region during December 2013 to November 2015.

(DOCX)

Click here for additional data file.

Average SST in the Niño (1+ 2) region, base periods of 30 years.

(DOCX)

Click here for additional data file.

10 Aug 2019

PONE-D-19-16590

The 2015-2016 El Niño increased infection parameters of copepods on Eastern Tropical Pacific dolphinfish populations

PLOS ONE

Dear Dr. Santana-Piñeros,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

As you will see, there are diverse opinions among reviewers regarding your study. However, there are two major concerns shared by all reviewers and myself: your study present correlative evidence of an association between parasite infection rates and El Niño temperatures, which cannot be used as an evidence of causality. You would need proper controls, longer time series, comparisons across species or experimental work to support your conclusion, otherwise you need to clearly state the limitations of your work. Also, your manuscript must be revised by an English native speaker before submitting your revised version.

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Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Partly

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Reviewer #1: Yes

Reviewer #2: I Don't Know

Reviewer #3: I Don't Know

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #2: Yes

Reviewer #3: No

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: General comments:

Santana-Pineros et al present a relevant study showing heightened prevalence and infection load of ectoparasitic copepods on dolphinfish during the recent severe El Nino in the TEP. I think the manuscript could use a careful edit by a native English speaker, I tried to assist as much as I could with grammar and spelling. Also data availability statement is made in the submission form, but there is no text in methods or elsewhere specifying where and how one could obtain raw data. Also mentioned are supplemental files for data and maybe some methods? Results? yet no supplemental files were in the pdf for review, nor are they cited anywhere in the text. The abstract needs to include specific values from the results section, not just increase/decrease statements. Finally, some restraint is warranted in extrapolating the data observed to draw general conclusions. While there was a clear correlation between parasite infection rates and El Nino, without proper controls or comparisons across species or multiple El Nino events it is difficult to attribute causation. For instance, in Figure 3A, it would appear to me that C. bonito prevalence is highly seasonal, rather than being directly driven by the El Nino event.

Once these issues are dealt with, and specific line comments (below) are addressed, I think this will be a good contribution for publication in PloS One.

Specific comments:

Line 39: Since study is specific to TEP, maybe restrain intro to TEP

Line 41: Parasites respond to environmental variations, but he influence of ENSO cycles on the seasonal variation of parasitic copepods has not yet been evaluated.

Line 45: ... in the dolphinfish Coryphaena hippurus and oceanography during the 2015-16 El Nino event. *** ENSO is not synonymous with El Nino, which is just one state or extreme of the ENSO cycle (which also includes La Nina on the opposite side of the spectrum). When referring to this event, please use El Nino or EN, not ENSO.

Line 46: Fish were collected from capture fisheries on the Ecuadorian coast (Tropical Eastern Pacific - TEP)

Line 47: Variation in sea surface temperature

Line 52: Of these, only SST increased consistently between February and November 2015

Line 55: both copepod species and increasing SST.

Line 57: Please state actual values by which prevalence and intensity of C. bonito and Ch. Quaternia increased. Also is this truly the only study that has looked at parasitic copepod abundance relative to sea surface temperature variation? Statements such as this throughout the MS should be carefully double-checked or re-worded.

Line 64: El Nino-Southern Oscillation (ENSO) events create fluctuations in sea surface temperature (SST) >0.5 �C in the Tropical Eastern Pacific (TEP). During El Nino events,…

Line 68: waters have a profound influence on local weather, ocean conditions, and marine and terrestrial ecosystems.

Line 69: Consider moving sentence on line 75 that starts “it has been suggested…” to before this sentence, since it provides precedent for climate change connection (having not been mentioned before this point leaves the reader bewildered)

Line 77: ENSO affects host-pathogen relationships of some marine organisms by reducing host immunity; consider citing recent paper on ENSO-fish disease in Galapagos (Lamb et al 2018 – Scientific Reports)

Line 80: fungal, viral, protozoan, or internal metazoan parasites;… such as metazoan ectoparasites, which are more exposed and infliuenced…

Line 86: Parasitic copepod loads have long been recognized as a factor affecting the growth, fecundity, and survival of both wild and farmed fish… NOTE: here you used the oxford comma (comma before “and” at the end of a list), whereas at other points in the MS you do not. The choice is up to you but please strive for consistency.

Line 88: to feed on their mucus, tissues, and blood, and leave open wounds exposing the host to secondary infections, leading to increased mortality…

Line 98: populations could be better managed in the region…

Line 104: moving northwest and the South Equatorial Current…

Line 109: phytoplankton, zooplankton, and pelagic fish communities

Line 113: SOI is listed here without previous mention or acronym definition; needs explaining

Line 114: we used a 2-year time series of monthly sea surface temperature…

Line 116:mWith prevalence and intensity of parasites in dolphinfish…

Line 117: Tropical Eastern Pacific during the El Nino event of 2015-2016.

Line 121: ….47 W), in the city of Manta, Manabi, Ecuador

Line 148: To calculate the sample size, we calculated the prevalence of both C. bonito and Ch. Quaternia in 154 individual hosts during pre-El Nino years. (Is this correct? Please be more detailed and specific how/why these fish were used as a baseline. What were the oceanographic conditions during the pre-collection phase relative to EN year?

Line 153: minimum monthly sample size to achieve what? Detect a single infection? Again please be specific.

Line 160: in plastic bags, labelled, and transported… for further microscopic examination

Line 171: citation should be for raw data, not package used to summarize it. Please find out where extraco3D acquires its datasets and cite them directly.

Line 185: Dolphinfish sizes were grouped into 10 cm total length bins in order to determine whether the size distribution of hosts varied between non- El Nino and El Nino periods.

Line 193: with monthly values of SST, salinity…

Line 211: Did you measure length, weight? Can you look at length/weight ratios and whether they varied between non – EN and EN periods, or any other parameter of body condition or physical health that could otherwise show an overall health effect of EN and/or copepod infection?

Line 216: ENSO periods do not affect host sizes or the size distributions of dolphinfish populations

Line 224: SST increased steadily from February 2015 until the end of the study, while

Line 227: and SOI 1+2 with no lag

Line 229: environmental variabiles in the Tropical Eastern Pacific

Line 233: by Fourier series (x-axis in months); (C) Spectral density of sea surface temperature… Fourier series (x-axis in months)

Line 239: with a mean intensity of … individual parasites per fish.

Line 241: … as did SST, Chl-A

Line 243: were observed with no lag; NOTE: continue this usage throughout (instead of “at lag 0”)

Line 245: mean intensity and SOI 1+2 with no lag. …a shift of SST variability related to the influence of SOI 1+2 coincident with changes in Chl-a and salinity, all of which affected the infection parameters of… NOTE: since these oceanographic factors co-varied you cannot partition the effects of each in this MS

Line 253: of prevalence (black line) and infection intensity… of C. bonito and sea surface temperature… cross-correlations between prevalence and infection..

Line 259: fluctuated over the two year period, with prevalence ranging 14-65%, and mean intensity ranging …

Line 264: salinity, and SST at a 4-month lag (again, use this annotation throughout)

Line 267: salinity and SST with no lag (Fig 4C). Since SST, Chla-a, and salinity co-varied over the study period, they may have acted simultaneously to trigger increased infection levels of Ch. Quaternia on C. hippurus. Since these oceanographic variables are highly correlated, it was impossible to detect the effect of each factor alone. … intensity and SOI 1+2 with a 4-month lag.

Line 278: SST (C), chlorophyll a (Chl-a)… and the prevalence and infection intensity…

Line 281: (ENSO) is one of the most dominant and consequential climate cycles on Earth… The EN (or El Nino, but not ENSO) phase… altering both environmental and biological oceanography.

Line 287: A specific case where extrapolation goes to far; correlation between ENSO and copepod infection prevalence does not signify causation

Line 289: Although we quantified seasonal and annual patterns of several oceanographic variables, only SST… was associated with the El Nino event of 2015-2016… average temperature relative to a 136-year record… SST for the global ocean was… Ocean temperatures during the first three months of 2015 were each the third warmest on record for their respective months

Line 305: and Chl-a on a roughly 11-month cycle

Line 307: parasitic copepod species might respond synergistically to two events: the increase in the number of host individuals *NOTE: this is the first mention of increased population size during El Nino, it is not reported on or shown in figures or tables in the Results section. Or are you referring to the citation on line 317? If so that citation should be mentioned before this statement.

Line 312: This sentence is almost illegible and I wouldn’t try to rewrite since I am unsure of the context. For this reason and myriad other small edits needed, I would again recommend the MS be carefully proof-read by a native English speaker.

Line 320: We documented … copepod species and SST. Our observations suggest that.. an increase in the prevalence and mean intensity…

Line 324: SST probably caused a faster and sustained increase…

Line 327: Rising infection parameters could be related to the higher number of suitable hosts due to high temperature *NOTE: again tenuous since you did not show data to support this…rate of infection between hosts, or increased reproduction rates of parasites due to high temperature.

Line 332: parasite infection is host fish population… copepod parasites, proximity…

Line 338: thus, with generalist parasites, a greater availability of oceanic hosts and both short and long-term shifts towards favorable environmental conditions, we expect…

Line 343: four months, in contrast to mean intensity, which showed an immediate response… triggers an increase in the… per infected host, which… * NOTE: Any evidence for Ch. quaternia to be in competition for space on hosts? Please cite authority on this statement.

Line 349: Additionally, this lag (up to 4 months)

Line 357: NOAA has already registered record SSTs evaluated during the 1880-2016 period

Line 361: by the Intergovernmental…

Line 365: showed the positive relationship between ENSO… and infection parameters… increase in water temperatures will influence… with negative effects on host organisms, modifying spatial range and seasonal abundances, and causing a rupture in biological interactions.

Line 371: especially in relevant fishing resource species, such as C. hippurus and other species… necessary to carry out long-term monitoring of this kind of parasite-host model to extrapolate the effects of environmental shifts on parasite-fish interactions.

Line 384: sampling permit

Figure 1 Decimal values should be labelled with a period, not a comma

Reviewer #2: Copepods are not convincingly presented to be good bioindicators.

The sampling number in the el nino period is less than the non el nino period.

The discussion is presented speculatively and the presentation of information is not in a logical sequence.

The main conclusion of the manuscript is that the increase in temperature in the el nino causes an increase in the copepod population, but in the graph it is verified the increase in temperature gradually, in other words, the peaks in the el nino do not seem significant to affirm that they influence the copepod population.

Reviewer #3: Dear Authors,

I have been asked to review your manuscript ‘El Nino increased infection parameters of copepods on Eastern Tropical Pacific dolphinfish populations’ (PONE-D-19-16590). The idea of testing the response of parasites to climate variability is very interesting, and I appreciate the amount of work you have put in the study. However, I have some major concerns (and a few minor comments) that first need to be solved before this manuscript can be accepted for publication.

First of all, I am afraid that your conclusion is not entirely supported by your analyses. You conclude that tropical parasites are sensitive to climate variability. However, you support your conclusion entirely correlative ‘evidence’. When there is a correlation between two variables (like SST and infection parameters) it does not necessarily mean that the sea surface temperature is responsible for increases in infections. It would have been better to analyze this with general additive models so you have a better idea of causality. Furthermore, it would be good for the manuscript to see some additional prove. For example, an experiment that shows that infective larvae have higher development rates with higher temperatures. There has been some speculation about this in the discussion (for other copepod species), but a small experiment would give the reader more confidence in your conclusion. In the discussion there is also speculation about an increase in host abundance as a result of higher temperatures. Are there not data (fish landings for example) to support this idea? In fairness, the discussion that should support your conclusions is way to speculative for the reader to believe that your conclusions are true and what the prime cause of your observations could be.

Second, the English of the manuscript is not good enough for publication. I highly recommend giving your manuscript to a native English speaker before submitting it again. In the minor comments section I will give some examples of sentences that were unclear to me. Here and there I have found also some Spanish words.

Third, the figures are too crowded. Having four different y-axes instead of one is very confusing. Also, Figure 2D, 3E and 4D require more explanation.

MINOR COMMENTS

L69: Climate change or ENSO?

L75/76: Please use ‘the’ before ENSO

L77: Change host-pathogens relations to host-pathogen relationships

L78: Remove ‘the’ before host immunity

L78/79: Change the virulence of pathogens to pathogen virulence

L80: Reference 10 goes before 25 and 56 (remove Table 1)

L83-85: Delete. This is too specific and exactly what you are going to do in this study.

L86: Substitute “load has long been recognized as a factor affecting” by “are known to affect”

L89: Substitute “leave” by “thereby leaving”. Substitute “exposing the host to” by “that can result in”

L113: This is the first time you use the abbreviations, please write out.

L115/116: This is the second time you use abbreviatons, please do not write out

L116: What exactly is the Southern Oscillation index? Please explain

L120: A fishing port is not really a study or sampling site. It’s a site where you collect the fish. Please change the title to “Collection of fish hosts”

L126: Remove title

L127_134: How are the fish caught? With nets? Long lines? Is there a chance that the parasites are removed by the fishing method?

L146: How many fish per month?

L147/148: Why are the lengths of the ENSO and non-ENSO period different?

L148: Substitute “calculated” by “calculate”

L148-155: This is very unclear to me. I had to read reference 14 to understand what you did. Please be more detailed here.

L161: Remove “All gills were dissected under a microscope”. You said the same before

L164: Increasing concentrations of glycerol. Please be more specific.

L165: I assume that the slides were also examined under a microscope. Please add this information

L175/176: I really do not know what you mean with these values and regions, and why they are important for your study.

L178/178/182: The websites are not working, please update the links

L185-187: Please rephrase.

L190: Single or Singular?

L193: Substitute “the monthly cycle of SST” with “the monthly patterns of SST”

L190-194: The part “for data with equally spaced sampling points in time” does not fit with the rest of the sentence. Please rephrase..

L215: Substitute “followed the same trend” with “was the same”

L216: Substitute “does” with “do”, “sizes” with “size”, “or” with “and”

L217: Dolphinfish populations

Fig 1: Please add unit to x-axis

L222: Ranged between

L222: What do the numbers between the barracks mean?

Fig 2: Please use the same x-axis for all the months

L243: What do you mean with lag 0? Please explain

Fig3A: How can the prevalence be higher than 100%? Please check your data

L296: “Each third warmest”. What do you mean?

L298: Add “resulting in” after “year”. Remove “evolved”

L307-312: Speculative. What proof do you have?

L312: “The current weakens system are often described” What do you mean?

L321: Replace “occurred” with “was observed”

L322: Place “the period” behind “Although”

L327: Substitute “Infection parameters rising” with “Higher infection levels”

L327: Suitable hosts

L328: Substitute “the high temperatures” by “higher temperatures”

L328: How much evidence do you have for this? Please give some sources

L331: So do you mean these are favorable temperatures or not? Please draw a conclusion here

L338-341: More a hypothesis than a conclusion how it is formulated here

L342-355: This does still not explain the lag phase between increasing intensity and prevalence. Do fish that are already infected become more infected?

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Reviewer #2: No

Reviewer #3: No

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15 Oct 2019

Thank you for your comments, which have contributed to improve the manuscript. In this new version we have supported the conclusions.

1) We have made a generalized additive model in order to determine if the El Niño event modifies the infection parameters.

2) We use “EN” instead of “SST”, since the infection parameters changed due to a set of variables that are modified by the EN event.

3) We included new information on the egg size and total length of copepods of the non-EN and the EN samples, in order to support the results of the manuscript.

4) The paper has been professionally proofread by an English native speaker before submission.

We hope that this new version will be good enough to be considered for publication in the journal Plos One.

Submitted filename: Response to reviwers.docx

Click here for additional data file.

5 Dec 2019

PONE-D-19-16590R1

The 2015-2016 El Niño increased infection parameters of copepods on Eastern Tropical Pacific dolphinfish populations

PLOS ONE

Dear Dr. Santana-Piñeros,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we still  feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Specifically, I fully agree with Reviewer 1, concerning the need to take into consideration the limitations of the data set (short as to assess effects of interannual ENSO variability) and the inherent limitation of correlative approaches to establish causative relationships between ENSO and biological factors). This manuscript would be improved if the limitations of the approach and data set are acknowledged and alternative explanations for the results are discussed.

We would appreciate receiving your revised manuscript by Jan 19 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Jose M. Riascos, Ph.D.

Academic Editor

PLOS ONE

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Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #4: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #4: Yes

**********

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Reviewer #1: Yes

Reviewer #4: Yes

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Reviewer #1: Yes

Reviewer #4: Yes

**********

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Reviewer #1: No

Reviewer #4: Yes

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Reviewer #1: please see attached for my general and specific comments regarding this resubmitted manuscript to Plos One

Reviewer #4: I have carefully read the paper as well as the comment made by the previous three referees. The authors have responded all the comments made by all of them. I only have one additional comment that does not prevent the publication of this manuscript. It is related with the period analysed because, bearing in mind the complexity of the studies about influence of climatic factors, global change, etc, the period analysed could be rather short. However, as I said before, the conclusions seem to be supported by the data and, due to the lack of studies in this particular issue of ectoparasites affecting marine resources and affected by oceanographic-atmospheric factors, the manuscript is valuable.

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Submitted filename: second review of dolphinfish EN parasites.pdf

Click here for additional data file.

18 Feb 2020

General comments:

This remains an interesting manuscript connecting a regional warming event to parasite loads in an important fishery species, making projections regarding effects of long-term climate change on the same. However, it also remains fraught with errors in English spelling and grammar, and fails to consider alternative hypotheses or the limits of the correlative evidence presented for mechanistic inference. For example, can you explore other potential hypotheses regarding the mechanism of host-driven increases in parasite loads during the dry season, when

hosts were smaller? Maybe they are less well fed and thus weaker in responding to parasites, or they are migrating from a different water mass during the dry season – maybe even representing a different host population? If you are consistently seeing smaller dolphinfish during the dry season I find it more likely that you are seeing different fish during this period of the year than that you are seeing the same population in both seasons and that these individuals are becoming smaller and then bigger again on a yearly basis. In addition, the seasonal pattern (dry/cold vs wet/warm) is very similar to the LN-EN difference in terms of water temperature, dolphinfish size, and infection parameters. This suggests similar driving mechanisms.

A= Thank you for your comments, which have contributed to improve the manuscript. In this new version we have include other potential hypotheses for explained our result. These changes can be observed in the section “infection parameters annual patterns”. Additionally, the paper has been professionally proofread by an English native speaker before submission

I hope that this new version will be good enough to be considered for publication in the journal.

Specific comments

Line 38: modified by El Niño, affecting several ecological processes. Parasites and other marine organisms respond to environmental variation, but the influence…

A = Done

Line 67: (and throughout) During El Niño (EN) events (no “the” before El or ENSO)

A = Done

Line 75: performance

A = Done

Line 121: both temperature ranges should be in low-high order, and you cannot cite a website directly in manuscript text (please see Plos One literature citation guidelines)

A= Done

Line 194: should this be a two-way ANOVA with season and EN as crossed or nested factors?

A = Changed “one” by “two”

Line 246: different (not difference)

A= Done

Line 333: This is the first tropical survey to provide evidence that the EN period promotes…

A = Done

Line 342: widely (not profusely)

A = Done

Line 348: Sentence needs to be re-written, whole document checked for basic English

A = We re-written sentence. Manuscript has been revised by an English native speaker

Line 351: although it prefers an SST range of 21-30 C

A= Done

Line 360: Sentence needs to be re-written

A= We re-written sentence

Line 375: missing a period

A= This sentence was eraser

Line 376: an historical event

A= Done

Line 385: My experience seeing fish in the water has been that larger animals tend to have far more ectoparasites than smaller individuals.

A= We explained this result in line 383 to 395

Line 416: Sentence needs to be re-written

A= We re-written sentence

Line 420: temperature on the copepod reproductive parameters of copepods; also this sentence is a run-on, with changes in tense that need to be corrected

A= We corrected this sentence

Line 454: Apparently; more frequent in the ??? no citation? And next line cites a website? Too many formatting, stylistic, and grammatical errors.

A= We corrected this sentence

Submitted filename: Response to reviwers.docx

Click here for additional data file.

18 Mar 2020

PONE-D-19-16590R2

The 2015-2016 El Niño increased infection parameters of copepods on Eastern Tropical Pacific dolphinfish populations

PLOS ONE

Dear Dr. Santana-Piñeros,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Academic Editor

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Please see the uploaded file for reviewer comments to the author for changes requested to MS text and methodology

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Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: Review of Dolphinfish.pdf

Click here for additional data file.

17 Apr 2020

Reply to referees’ comments. Each query is followed by an answer (A).

General comments:

Santana-Piñeros et al. have submitted their revised version of a study investigating the effects of the 2015-16 El Niño event on ectoparasite loads of dolphinfish. The manuscript has been thoroughly revised and most of the grammatical/English issues have been corrected (a few minor changes still needed, see specific comments). In addition, the authors have modified their language to consider a more nuanced explanation of the environmental factors driving variation in ectoparasite infection rates, in light of the relatively short sampling window around the major EN event.

For the most part I feel that our issues raised have been dealt with. However, there are still some inconsistencies/shortcomings in the interpretation of the results. For instance, the bulk of the article (including the title!) suggest that EN increased infection parameters of copepods on dolphinfish, yet in the discussion (see lines 420-421), you state that infection rates of C. bonito were actually higher during the non-EN period.

A= Thank you for your comments, which have substantiallyt improved the manuscript.

We have reviewed the statiscal analyzes presented in the previous version of the manuscript and detected a mistake in the SST values, which were for the 3.4 region and not 1+2 region. We have corrected it and the generalized models showed a higher explained deviance and even the prevalence of C. quaternia could be explained. Our results confirmed that the increase in SST has risen the infection parameters of the two parasite copepods (see Figs. 3D, 4D). In this new version, we re-written the paragraph (lines 427-439) and we have included a figure in a supplementary file.

In addition, you state that mean host TL did not differ between EN and non-EN periods, but then in the discussion (e.g., line 427) you use increased TL during EN as an explanation for decrease in C. bonito infection during EN. If you truly think that host size was an important factor interacting with the oceanographic variables to predict infection rates, you might consider analyzing different size classes separately.

A= This argument was removed from the manuscript. We separately analyzed different size classes and there were no differences in prevalence with respect to the previous analyzes.

Finally, I have some doubts about the spectral analysis methodology. Since this is a relatively short window of time (24 months), a peak spectral density of 11 months is nothing more than saying that one year was different from the next. This alludes to my original concern with this manuscript, that the short sampling period is insufficient to establish an EN effect per se, but rather a difference between years that might be explained by oceanographic parameters. For this reason I wonder if ONI is really an informative explanatory variable or if you should simply focus on SST, salinity, etc.

A= Spectral analysis methodology does not allow comparison between years, but repeated patterns over time. The longer the time series, the different time patterns can be detected. Due to our short time series, the spectral analysis detected that every 11 months the environmental variability in the study area is repeated, which is consistent with the oceanographic temporality in that area. The difference between years was given by the SST, with higher values in 2015 (Fig. 2). In this sense, we rewrote the paragraph taking the reviewers' suggestion, focusing on explaining the results with SST and not ONI.

Specific comments

Line 39: the influence of the EN cycle… (“the” is placed before EN in this case)

A= Done.

Line 44: since the term “TEP” does not appear later in the abstract, no need to define acronym here (just say Tropical Eastern Pacific). Acronym is correctly defined in the main body of the text on line 65.

A= Done.

Line 51: Consider reporting specific number of degrees C SST increase here (rather than just “SST increased consistently”)

A= We add information in abstract (Lines 48-56) and include a specific value of SST (Line 57).

Line 52: “The SST increase interrupted the seasonal patterns of salinity and Chl-a. It is suggested that EN had the greatest influence on the infection parameters of both copepod species.” -- These two sentences do not make sense and do not add information to the abstract. You state in the previous line that only SST increased over the EN period, and the entire paper is about the influence of EN on infection parameters of copepods. I recommend removing these two sentences and beginning next sentence with simply: “We observed…”

A= We deleted those lines and modified part of the abstract, showing the most important results of the manuscript.

Line 64: Indent first sentence of each paragraph (see throughout MS), and in this case it is correct to start with “The El Niño…”

A= Done.

Line 74: “Affects performance, population dynamics…”

A= Done.

Line 100: Risso, 1810 is placed in parentheses while other citations of authorities who named species were not in parentheses; please be consistent

A= International Code of Zoological Nomenclature (ICZN) establishes: In citing the name of an author, the surname is given in full, not abbreviated. The date of publication in which the name was established is added for example Mugil curema Valenciennes, 1836. However, if species was described with other genera, the author and year are set in parentheses. For example, Katsuwonus pelamis (Linnaeus, 1758) was described as Scomber pelamis Linnaeus, 1758. Since the taxonomic status of A. rochei changed, then it is mandatory to have the surname in parenthesis.

Line 119: SST was defined earlier, can simply use acronym throughout manuscript

A= Done.

Line 135: … sampling of 154 dolphinfish to establish a baseline prevalence of infection during the non-EN period

A= Done.

Line 156: using specific literature taxonomic keys

A= Done.

Line 170: the EN conditions

A= Done.

Line 174: Values of the SST

A= Done.

Line 238: (mean 72.88 ± 12.45 SD) this is to define parameters upon first usage, can leave following values as numbers without units

A= Done.

Line 271: Please define UPS acronym upon first usage (for salinity)

A= Done.

Line 272: Please state which season and/or EN/Non-EN periods had greater/lower values for each of the environmental parameters measured (rather than just stating that they were significantly different)

A= We changed paragraph.

Line 291: 29% - 100%

A= Done.

Line 330: altering both environmental physical and biological oceanography

A= Done.

Line 341: Results (mean? TL in dry and rainy seasons) should be presented in the Results section

A= We delete this phrase.

Line 345: Can you discuss the approximate ages associated with these sizes? Are you suggesting these fish are being born and growing to maturity within a single season? Or are larger individuals migrating into these waters during the rainy season?

A= We cannot associate size classes with ages. We re-wrote this paragraph.

Line 358: I have a hard time interpreting the 11-month cycles statement. With only 24 months of data, you can really only say that one year was different from the next.

A= The time series detects patterns over time. In this sense, we do not say that one year is different from other, but that the variability of our oceanographic variables is repeated in 11-month cycles. These cycles are consistent with the dynamics of currents and seasonal temporality in the area.

Line 360: varies varied

A= Done.

Line 398: hosts

A= Done.

Line 407: dynamics of the parasites

A= Done.

Line 418: these are different mean SST values reported as long-term averages for these months than those reported on line 120

A= We change SST by air temperature in line 120.

Line 420-421: This statement runs directly in opposition to the title of the paper

A= We modified this statement.

Line 465: density-dependence, intra- and inter-specific competition,

A= Done.

Line 469: The future ENSO events

A= Done.

Submitted filename: Response to reviwers.docx

Click here for additional data file.

22 Apr 2020

The 2015-2016 El Niño increased infection parameters of copepods on Eastern Tropical Pacific dolphinfish populations

PONE-D-19-16590R3

Dear Dr. Santana-Piñeros,

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Jose M. Riascos, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

27 Apr 2020

PONE-D-19-16590R3

The 2015-2016 El Niño increased infection parameters of copepods on Eastern Tropical Pacific dolphinfish populations

Dear Dr. Santana-Piñeros:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

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PLOS ONE