Endemic Shearwaters Are Increasing in the Mediterranean in Relation to Factors That Are Closely Related to Human Activities

Global Ecology and Conservation 20 (2019) e00740

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Global Ecology and Conservation

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Original Research Article Endemic shearwaters are increasing in the Mediterranean in relation to factors that are closely related to human activities

* Beatriz Martín a, , Alejandro Onrubia a, Miguel Ferrer b a Fundacion Migres, CIMA, ctra. N-340, Km.85, Tarifa, E-11380, Cadiz, Spain b Applied Ecology Group, Donana~ Biological Station, CSIC, Seville, Spain article info abstract

Article history: The aim of this study was to estimate global population trends of abundance of two Received 20 March 2019 endemic migratory seabird species breeding in the Mediterranean Sea, Balearic and Received in revised form 22 July 2019 Scopoli's shearwaters, from migration counts at the Strait of Gibraltar. Specifically, we Accepted 31 July 2019 assessed how regional environmental conditions (i.e. sea surface temperature, chlorophyll a concentration, NAO index and fish catches), as proxies of climate change, prey availability Keywords: and human-induced mortality factors, modulate the interannual variation in shearwater Chlorophyll numbers. The change in the migratory population size of both shearwater species was Climate change fi Fisheries estimated by tting Generalized Additive Models (GAM) to the annual counts against the fi Seabird year of observation. Speci cally, we modelled daily counts of migrant shearwaters during Monitoring the post-breeding season. Contrary to current estimates at breeding colonies, coastal-land based counts of migrating birds provide evidence that Baleric and Scopoli's shearwaters have been recently increasing in the Mediterranean Sea. Our results highlight that demographic patterns in these species are complex and non-linear, suggesting that most of the increases have happened recently and intimately bounded to environmental factors, such as chlorophyll concentration and fisheries, that are closely related to human activities. Counts of migrating birds at strategic coastal points may provide useful estimates of the global population trend, as well as an efficient and rapid assessment of these and other seabird species in the Mediterranean. © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction

Seabirds are top predators at the end of the aquatic trophic chain thus they are of main interest for monitoring the marine environments, since they are good indicators of the status of pelagic ecosystems and the changes therein (Zacharias and Roff, 2001). Therefore, the standardized long-term monitoring of these species may be a useful tool to detect alterations in ﬁsheries and/or changes in marine environments due to climate and other human-induced changes (Martín et al., 2016). In addition, many of these species are endangered thus they require accurate estimates of population trends to detect any change in their conservation status (IUCN, 2001; Paleczny et al., 2015). In this sense, many of the efforts made to date to monitoring seabird populations have been devoted to census of breeding numbers with some exceptions (e.g., Aunins et al., 2013; Karris et al., 2017). The main reason is because it is easier, both logistically and in terms of the costs required to survey and monitor, to

* Corresponding author. E-mail address: [email protected] (B. Martín). https://doi.org/10.1016/j.gecco.2019.e00740 2351-9894/© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/). 2 B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740 make accurate counts of breeding birds or nests, than it is to count all birds in seabird populations (Furness et al., 2003). However, changes in breeding numbers may not reflect overall population trends, since they do not provide information on the non-breeding part of the population (i.e., immature birds and mature non-breeding birds; Arroyo et al., 2014; Weimerskirch et al., 1997). In addition, changes in the timing of breeding can be misinterpreted as changes in population numbers when counts are carried out on a particular same date during the breeding period. Moreover, even when monitoring is focused on breeding numbers, surveillance of seabirds is still logistically costly, thus long-term monitoring of seabird populations is scarce (Becker and Chapdelaine, 2003), and the available information about population trends of seabird species is frequently incomplete or inaccurate (Carboneras et al., 2013). However, many seabirds are migratory species, thus sampling their numbers during migration may offer a cost-effective and efficient method for monitoring overall populations of these species (Arroyo et al., 2014) compared to more direct methods such as nest surveys or sampling breeding numbers (Lewis and Gould, 2000). The Strait of Gibraltar (southern Spain) is a bottleneck used by many seabird species breeding in the Mediterranean Sea, since it is the only connection between the Atlantic Ocean and the Mediterranean Sea (Tellería, 1981). Consequently, this area is a key point for monitoring seabird populations during their migratory trips, moving in or out the Mediterranean throughout their annual cycle (Hashmi, 2000) by means of visual observation of migration (Arroyo et al., 2014). Most of the population of Balearic shearwater (Puffinus mauretanicus) and the entire population of Scopoli's shearwater (Calonectris diomedea) leave the Mediterranean each year after breeding, passing along the Strait of Gibraltar (Guilford et al., 2012; Reyes- Gonzalez et al., 2017) and spend the non-breeding season in the Atlantic. The Balearic shearwater only breeds in the Balearic Islands (Spain) and it is considered as one of the most threatened seabirds in the world, included as ‘Critically Endangered’ on the IUCN Red List (BirdLife International, 2018a). Scopoli's shearwater is globally considered as “least concern” (BirdLife International, 2018b) but it is an endemic breeding species in the Mediterranean included as ‘Endangered’ in the Bird Red Data Book for Spain (Carboneras, 2004) because their populations are believed to be declining (Carboneras et al., 2013; Derhe, 2012). Both shearwater species are also considered as threatened birds at the European level (i.e., rare or vulnerable bird species as listed in Annex I of the EU Bird Directive). However, there is no systematic global monitoring scheme for any of these species (BirdLife International, 2018b, 2018b). Estimates of population trends for Scopoli's shearwater are based on data from only 6% of the population (Carboneras et al., 2013; Derhe, 2012). In the case of Balearic shearwater, counts at the breeding sites rely on indirect sampling methods (e.g. counts of rafts, vocalizations) due to the inaccessibility of the breeding sites, and therefore the population estimates are highly inaccurate, not allowing to derive reliable population trends (BirdLife International, 2018a). Counts of migrating birds at bottlenecks may allow us to detect overall population trends of these two seabird species and these trends can be used as an early warning system to identify conservation concerns at regional level related to environmental changes such as global warming or fisheries, among others (Martín et al., 2014; Paleczny et al., 2015). The aim of this study was to estimate global population trends of abundance of two endemic migratory seabird species breeding in the Mediterranean Sea, Balearic and Scopoli's shearwaters, from migration counts at the Strait of Gibraltar. Previous studies support the relationship between food availability and population size in seabirds, through effects on the reproductive output and the survival of these species (Croxall and Rothery, 1991; Oro and Furness, 2002). In addition, since migrating birds need to replenish energy reserves during stopover periods at key locations where maximize their refueling opportunities (McKnight et al., 2013), fluctuations in migration are also related to changes in food resources (Wynn et al., 2007). Moreover, in some seabird species, such as Scopoli's shearwaters, it is known the relationship of survival and breeding success with climate indexes such as NAO and SOI (Genovart et al., 2013b), likely through effects of these indexes on fish stocks (Tsikliras et al., 2018). Therefore, to better understand the fluctuations observed in migration counts, we collected information on the annual variation of shearwater food resources. Specifically, we assessed how regional environmental conditions (i.e. sea surface temperature, chlorophyll a concentration, NAO index and fish catches), as proxies of climate change, prey availability and human-induced mortality factors, modulate the interannual variation in shearwater numbers. Finally, we fully discuss our findings in relation to changes in the global population of shearwaters.

2. Methods

2.1. Study area

The Strait of Gibraltar is a short sea-crossing point for pelagic seabirds (14 km between Europe and Africa) where migrants are constrained from both shorelines into a narrow front. Since the Strait is the only connection between the Atlantic Ocean and the Mediterranean Sea (Fig. 1), it funnels seabirds moving in or out the Mediterranean throughout their annual cycle (Hashmi, 2000). Therefore, this site records east-west oriented movements of seabirds passing through the site both in spring and autumn. During the post-breeding period, seabirds migrating along the Spanish coast of the Strait of Gibraltar tend to concentrate nearer the shoreline than randomly expected (Mateos et al., 2010; Mateos and Arroyo, 2011), thus they can be observed from land-based observatories in the coast (Arroyo et al., 2014). Particularly, Balearic shearwater has a coastal migratory pattern closely following the Spanish Mediterranean coast (Hashmi, 2000; Mateos and Arroyo, 2011). In contrast, although most of the migration of Scopoli's shearwater seems to occur predominantly along the south coast of the Strait (Navarrete, 2008), this migration is also visible far off the coast from Tarifa (Mateos and Arroyo, 2011) due to the narrow strip of water that separates both northern and southern coasts at this point. We conducted shearwater counts from a vantage B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740 3

Fig. 1. Study area. Location of the coastal-land based counting site in the southern end of the Tarifa Island.

point in the southern end of the Tarifa Island (360002.9600N, 0536036.5100W), the southernmost point of the north coast of the Strait of Gibraltar, at about 5 m above sea level. Data collection protocol. Migration monitoring may allow us to detect population trends over large geographic areas because the pattern of change in migrant counts is expected to follow the pattern of change in population size. But temporal patterns of relative abundance in count data are descriptive of corresponding patterns in populations only when the proportion counted is constant through time. To ensure that this condition is met, annual counts must be recorded with data collection standardized protocols that are repeated from year to year (e.g., Martín et al., 2016). Long-term data counts of post-breeding migrating seabirds along the Strait of Gibraltar have been collected in Tarifa Island since 2005 to date. Counts were conducted on an annual basis over the entire post-breeding migration. According to the particular migration phenology of both species, daily counts were carried out between 06h00 and 11h00 UTC, and from mid-May to mid-July, in 2007e2018 in the case of Balearic shearwater. In contrast, for recording Scopoli's shearwaters we conducted counts in 2005e2018, between 06h00 and 13h00 UTC, from October to November. Annual counts were recorded with data collection standardized protocols that are repeated from year to year (Arroyo et al., 2014). Counts were carried out by a minimum of two observers with at least one of the observers being a trained ornithologist. In this way, we avoid long-term trends in observer efficiency that could bias our trend estimates (Farmer et al., 2007; Nolte et al., 2016). All observers were equipped with telescopes (magnification 20) and binoculars (10 42). The main observer conducted continuous counts by scanning the sea area in front of the count site using the telescope while a secondary observer surveyed those birds out of the field of view of the telescope and not detected by the main observer using the binocular. Both observers alternate these roles during the observations (Nichols et al., 2000). This double-observer protocol allows to control observer efficiency and to minimize biases in counts due to the variation in detectability (Nolte et al., 2016). With the optics applied we estimate a coverage ranging from the shoreline out to sea from 100 m to 3000 m (Arroyo et al., 2014), depending on the visibility conditions. This coverage comprises about 90% of the shearwater flocks flying along the Strait (Mateos and Arroyo, 2011). Number and flight direction of the observed birds was recorded. We also recorded hourly wind direction (cardinal direction) and speed (Beaufort scale) using an on-site measuring station located in the counting site. Daily monitoring effort (counting time per day) was equal across the years. For Balearic shearwaters, counts were conducted on a continuous basis during the daily monitoring period, whereas for Scopoli's shearwaters, counts were carried out in 10-min sequences, three sequences every hour. However, counts were not conducted on days with persistent rain. There is no systematic effort for disentangling whether Calonectris sp. individuals at the Strait are the Atlantic (Cory's, C. borealis) or the Mediterranean (Scopoli's, C. diomedea) shearwater species. However, in 2018 we photographed flocks of Calonectris sp. individuals along 14 days covering the post-breeding migration period. From these photographs we could estimate the proportion of birds belonging to one or the other species migrating along the Strait of Gibraltar. The identifi- cation of the individuals depicted in the photographs was made afterwards by an expert ornithologist with more than 10 years of experience observing these species, and it was based on the morphological traits of the birds. 4 B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740

2.2. Model variables

Effective monitoring effort (number of counting hours in the case of Balearic shearwater, number of 10-min sequences in the case of Scopoli's shearwater) was taken into account in the models through additional variables. Bird records were only considered for analysis if they were assigned an east-west oriented movement (output flow from the Mediterranean Sea into the Atlantic Ocean). According to previous studies, most of the seabird flights followed E-W and there were no signals of birds following NEeSW direction of the shoreline to the East of Tarifa (Mateos and Arroyo, 2011), thus birds did not appear to turn back on the other side of the Strait. Counts of birds in migratory bottlenecks are subjected to biases related to observer-dependent errors that can be confounded with the true environmental source of variation (Farmer et al., 2007). In addition, daily migration counts may have a highly skewed distribution caused by weather and seasonal variation in the number of migrants (Francis and Hussell, 1998). By means of a standardized data collection, we may reduce at a minimum this variance, but we cannot completely remove the between-year variation in the migrant count data (Dunn, 2005). By including main sources of bias in the models as predictors (visibility, wind speed and direction, cloud cover, estimated distance between observer and bird) through information that was collected during the sampling, we can control the effects of these errors on the counts. Modelling these effects to adjust the trend estimates has been shown to be an effective method to control for the variation in detectability when migrating birds are recorded at fixed observation points (Nolte et al., 2016). Cloud cover, visibility and distance was estimated by the observer according to discrete categories previously defined. Hourly wind direction (cardinal direction) and speed (Beaufort scale), at c.10 m above sea level was measured with an on-site measuring station at the counting site. Meteorological variables such as wind, precipitation and temperature may also influence migratory phenology and the number of birds departing Mediterranean each year (Guilford et al., 2012; Jovani and Grimm, 2008). Daily wind speed was measured as an average of hourly wind speed measurements. For wind direction, we split wind in east-west and north-south components and then we quantified the proportion of the hourly records for each wind component during the daily monitoring period. In order to complement the information provided by the previous variables, we also include as model predictors daily precipitation and temperature (minimum and maximum daily temperatures) sourced from the Spanish Meteorological Agency (AEMET, https://opendata.aemet.es/). Date of passage (i.e., julian date) was other predictor included in the models. Climate change is known to have effect on the migration phenology of many different bird species (Rubolini et al., 2007; Vegv ari et al., 2010). In order to account for climate change effects, we quantified an average sea surface temperature (SST) anomaly during the breeding season for each particular year. To take into account all fractions within the migratory population (not only adult breeders and juveniles but also immature birds and non-successful breeders) we defined the breeding season as the period from first laying date to date of first migrating individuals observed in the study area: February to April in the case of Balearic shearwater; from May to September in the case of Scopoli's shearwater (Arroyo et al., 2014; Hashmi, 2000; Oro et al., 2016; Reyes-Gonzalez and Gonzalez-Solís, 2016). Temperature anomaly was derived from the global HadCRUT4 dataset which provides monthly averages of sea surface temperature anomalies for the Northern hemisphere (Hadley Centre, Kennedy et al., 2011). SST anomalies are expressed as anomalies from 1961 to 1990 (Climatic Research Unit, University of East Anglia; https://crudata.uea.ac.uk/cru/data/temperature/#datdow). Average monthly NAO index during shearwater breeding season was derived from the Climate Prediction Center (US National Weather Service, NOAA), as monthly data from 1950 to 2018 (http://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml). Balearic shearwater's diet includes small pelagic fish and demersal fish frequently obtained from trawling discards, but it also feeds on plankton and macrozooplankton, specifically krill (Arcos and Oro, 2002; Louzao et al., 2015). In contrast, most of the Scopoli's shearwater preys are fishes, although they also feed on squids (Granadeiro et al., 1998; Xavier et al., 2011) and can make use of fishing discards (Bartumeus et al., 2010; Cortes et al., 2018; Karris et al., 2018; Soriano-Redondo et al., 2016). Although precise data on food availability and their year-to-year variation are hard to obtain in natural conditions, we included in our models two proxies of food availability for shearwaters: phytoplankton biomass and fisheries. Specifically, we used algal biomass (chlorophyll concentration, Chla in mg.m-3) as a proxy for phytoplankton biomass. Moreover, the direct relationship (i.e., relationship without any time lag) between chlorophyll concentration and the abundance of the main shearwater preys (i.e., small pelagic fishes) has been shown in multiple studies (e.g., Abdellaoui et al., 2017; Diankha et al., 2013; Dutta et al., 2016; Pitchaikani and Lipton, 2012). We obtained chlorophyll concentration as the product from satellite-based optical sensors (Gons et al., 2008) monthly available at 4 km resolution for 2003e2017 period (JRC Data Catalogue; http://gmis.jrc.ec.europa.eu/satellite/4km/). For Balearic shearwater, we considered average chlorophyll concentration at the Balearic FAO fishing Division area 37.1.1, mainly overlapping with the breeding area of this shearwater species. For Scopoli's shearwater, chlorophyll concentration values were based on average values for the Mediterranean Sea, covering the following FAO fishing Division areas: Balearic (Division 37.1.1); Gulf of Lions (Division 37.1.2), Sardinia (Division 37.1.3), Adriatic (Division 37.2.1), Ionian (Division 37.2.), Aegean (Division 37.3.1) and Levant (Division 37.3.2), coinciding with the breeding range of this species. Specifically, average chlorophyll values were measured during the breeding season previously defined for both species. Since survival of seabirds will depend not only on the environmental conditions during breeding, but also on those occurring after breeding (Furness et al., 2003), we also considered chlorophyll concentration average values for the migration period at the study area (May to July for Balearic shearwater; October to November for Scopoli's shearwater; Arroyo et al., 2014; Hashmi, 2000). Information on fisheries was obtained from annual records of capture statistics by areas and species provided by the General Fisheries Commission for the Mediterranean (GFCM; http://www.fao.org/gfcm/data/ B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740 5 capture-production/en/). From this database, covering years from 1970 to 2016, specifically we selected fishes, cods, octopuses and cuttlefishes, excluding tunas, other mollusks, corals, crustaceans, turtles, sponges, urchins and other invertebrates. Fishing areas based on the breeding range of both shearwater species were also selected based on FAO fishing areas as described above for chlorophyll concentration (Table 1).

2.3. Statistical analysis

The change in the migratory population size of both shearwater species was estimated by fitting Generalized Additive Models (GAM (Hastie and Tibshirani, 1990); to the annual counts against the year of observation. Specifically, we modelled daily counts of migrant shearwaters during the post-breeding migration. The GAM's included negative binomial response and a log link function, using package mgcv (Wood, 2011)inR(R Development Core Team, 2018). Using GAM models, we could compensate for missing counting days for Scopoli's shearwater in 2014, and for the lack of data in the annual count series of Balearic shearwater in 2013, 2015 and 2016 (Arroyo et al., 2014; see Fig. A1 in the supplementary material). To avoid collinearity, from the total set of environmental predictors (Table 1) only uncorrelated variables (i.e., non-significant Pearson correlation coefficient between pairs of variables) were kept in the models. In case of correlation was detected, from each pair of correlated variables we kept the most correlated variable to shearwater abundance. Restricted maximum likelihood (REML) was used as method for smoothing parameter estimation in order to avoid overfitting (Wood, 2011). Splines were only calculated for those predictors that, after a preliminary inspection, showed non-linear relationships with shearwater counts. Akaike's information criteria (AIC; Akaike, 1973) was used for model selection. If several models had low and similar AIC values (Delta AIC<2) then we selected the most parsimonious one (Burnham and Anderson, 2002). Autocorrelation can result

Table 1 Description of the predictors included in the GAM and GAMM models for Scopoli's and Balearic shearwaters.

Predictor Description Source effort Daily monitoring effort Sequences for Scopoli's and hours for Balearic shearwaters, respectively; see Methods. visib Mean hourly visibility (based on four different visibility categories e Estimated by the observer at the counting site from complete visibility to null visibility) estimated by trained observers dir.W Proportion of hours/sequences with western winds (western, Measured at the counting site (weather station) northwestern and southwestern winds) dir.Ea Proportion of hours/sequences with eastern winds (eastern, Measured at the counting site (weather station) southeastern and notheastern winds) dir.N Proportion of hours/sequences with northern winds (northern, Measured at the counting site (weather station) northwestern and northeastern winds) dir.Sa Proportion of hours/sequences with southern winds (southern, Measured at the counting site (weather station) southwestern, southeastern winds) Dis Distance to the bird flock estimated by the observer at the counting Estimated by the observer at the counting site site (Mateos et al., 2010) prec Precipitation (mm) Spanish Meteorological Agency (AEMET, https://opendata.aemet.es/ ). Data from Tarifa meterological station. year Year of the observation Measured at the counting site julian Day (julian date) of the observation Measured at the counting site wind Mean hourly wind speed (Beaufort scale) Measured at the counting site cob Mean hourly cloud coverage (based on visibility categories estimated Estimated by the observer at the counting site by trained observers: 0%, 20%, 40%, 60%, 80%, 100%) tmin Daily minimum temperature (C) Spanish Meteorological Agency (AEMET, https://opendata.aemet.es/ ). Data from Tarifa meterological station. tmaxa Daily maximum temperature (C) Spanish Meteorological Agency (AEMET, https://opendata.aemet.es/ ). Data from Tarifa meterological station. chlorophyll Chlorophyll concentration (Chla in mg.m-3) as the product from Gons et al. 2008. JRC Data Catalogue; http://gmis.jrc.ec.europa.eu/ satellite-based optical sensors at 4 km resolution (mean values satellite/4km/ across breeding areas during the breeding period; see Methods). chlorophyll- Chlorophyll concentration (Chla in mg.m-3) as the product from Gons et al. 2008. JRC Data Catalogue; http://gmis.jrc.ec.europa.eu/ 2a satellite-based optical sensors at 4 km resolution (mean values satellite/4km/ across breeding areas during the migration period; see Methods). fisheries Annual records from fishing capture statistics in the breeding areas General Fisheries Commission for the Mediterranean (GFCM; http:// (i.e., fishes, codes, octopuses and cuttlefishes; see Methods). www.fao.org/gfcm/data/capture-production/en/) SST Average of sea surface temperature anomalies (SST) for the Northern HadCRUT4 dataset (Hadley Centre, Kennedy et al., 2011). hemisphere, expressed as anomalies from 1961 to 1990 (mean of Climatic Research Unit, University of East Anglia (https://crudata. spring SST; see Methods) uea.ac.uk/cru/data/temperature/#datdow). NAO NAO index, monthly data from 1950 to 2018 Climate Prediction Center (US National Weather Service, NOAA) (http://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao. shtml).

a tmax was highly correlated with tmin, and chlorophyll concentration during migration was correlated with chlorophyll concentration during breeding (r > 0.9, p < 0.001), dir. E with dir. W, and dir. S with dir. N, thus only tmin, chlorophyll during breeding, dir. W and dir. N were retained for model selection (see Methods for a description of the variable selection procedure). 6 B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740 in exaggerated magnitudes or too low significance for trend estimates. Temporal autocorrelation (ACF) and partial temporal autocorrelation (PACF) functions for the models were inspected in order to determine the presence of a temporal autocorrelation structure thus, in case any significant autocorrelation was detected, this autocorrelation structure could be specified (Box et al., 2008) by means of Generalized Additive Mixed Models (GAMM) in mgcv package in R. In this case, we measured a random effect (random slope) for time (i.e., day) at the year level, which means that the slope across days varies across years. Specifically, we assessed whether the effect of day (julian date) on counts (the slope) differed across years, being indicative of the trend researched for. Therefore, in the GAMM model we did not fit an annual trend, but an interaction between day and year. The best model structure among the different ARIMA models was also determined using AIC by means of the package forecast (Hyndman and Khandakar, 2008)inR.

3. Results

Our results showed that most shearwater movements in the Strait occurred during the first half of the day (see Fig. A2 in the supplementary material), supporting the appropriateness of the daily counting period. Similarly, seasonal counting period mostly covered the total migration timing of the two species along the Strait of Gibraltar (Fig. A3 in the supplementary material). Compared to Scopoli's shearwater, the variation in Balearic shearwater counts was high, both in terms of date and magnitude, from one year to another (Fig. A3 in the supplementary material). Maximum and minimum daily temperatures (r ¼ 0.92; p < 0.001), and chlorophyll concentration during breeding and migration periods (r ¼ 0.98 and r ¼ 0.96, for Balearic and Scopoli's shearwaters, respectively; p < 0.001) were highly correlated, thus only minimum temperature and chlorophyll during breeding were kept for model selection. The inspection of quantile-quantile plots of the residuals of the best fit models (Gordon et al., 2015) for both shearwater species showed a good agreement between the distribution of our count data and the expected negative binomial distribution (i.e., data laid close to the 1:1 line in both species). Temporal autocorrelation functions (ACF and PACF) for the GAM models showed no significant autocorrelation at any time lag for Scopoli's shearwater (see Fig. A4 in the supplementary material). However, Balearic shearwater counts required of a GAMM model with a temporal correlation structure. This correlation structure contained an ARMA (2,2) process (see Table A1 in the supplementary material) nested within year, which suc- cessfully accounted for the autocorrelation presented in the time series (Fig. A5 in the supplementary material). Due to the form of the correlation term, in this GAMM model year became a random effect thus this variable had to be removed from the fixed effect terms. Therefore, in the GAMM model we did not fit an annual trend, but an interaction between day and year (i.e., the random statement measured the variance in the effects of day on shearwater abundance across years). According to the GAMM model for the Balearic shearwater, each year's slope of the random effect differed from the average slope (i.e., the variance estimate for the random slope is different from 0), supporting that the effect of time (day) on shearwater abundance was different across years (i.e., the slope of time was not the same for all years). Since there was a significant effect of year in the random model and the significance and the magnitude of the coefficients in GAMM and GAM models for Balearic shearwater were highly consistent (see Table 3a and Table A2 in the supplementary material), for the sake of simplicity of the reported results, we provided the temporal trends measured on the GAM model (Tables 2a, 3a and 4a; Fig. 2a). According to best-fit GAM models (Table 2), both shearwater species showed significantly non-linear increasing trends during the study period (Table 3). Specifically, shearwater abundance exhibited a fall and then a rise in relation to regional environmental conditions, mainly to the fish catches and the chlorophyll level (Figs. 2 and 3), indicating that most of the increases have happened recently (from 2012; Fig. 2). The annual average rate of change of the virtually linear segment for the period 2012e2018 (derived from model predictions as the slope of the segment connecting these two specific year points on the predicted curve; Fig. 3, variable “year”), was about 44 and 5 birds in Scopoli's and Balearic shearwaters, respectively. Apart from year of the observation, western winds, sampling effort and day of observation were the significant variables predicting Balearic shearwater abundance during migration, whereas Scopoli's shearwater abundance was affected by sampling effort, visibility, precipitation, wind speed, temperature, year and day of the observation. Since regional predictors (i.e., chlorophyll concentration, surface temperature anomaly, fisheries) were correlated with each other, and specially with year (see Table A3 in the supplementary material), these variables were alternatively tested in separate GAM models in both shearwater species. Alternative models fitted with different regional predictors showed that annual trends in Balearic shearwater were mainly mediated by fisheries and, to a lesser extent by chlorophyll concentration during spring, whereas for Scopoli's shearwater, chlorophyll concentration appeared to be the better predictor for the interannual variation (Table 4 and Table 5). Compared to these models, the models including the surface temperature anomaly (SST) and the NAO index showed much lower AIC value in both shearwater species. The visual inspection of the flocks of Calonectris sp. depicted in the photographs took over the post-breeding migration in 2018 (see Table A4 in the supplementary material) showed that Cory's shearwaters represented only 1% of the overall total of Calonectris sp. individuals.

4. Discussion

Our results show that counts of migrating Balearic and Scopoli's shearwaters have significantly increased in the last decade, specifically during 2012e2018. According to our findings, food availability in their breeding areas at the Mediter- ranean Sea, as well as direct and indirect impacts of fisheries, seem to have driven the dynamic of the migratory population B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740 7

Fig. 2. GAM model predictions of annual trends in shearwater abundance at the Strait of Gibraltar over the season (“julian”). Predicted values from the best-ﬁt models with a quadratic effect of “year”. Values for all other predictors in the models (see Table 3) have the closest observed value to the median. Data for 2005e2018. (a) Balearic; (b) Scopoli's shearwaters.

trends in these species (Ramírez et al., 2016; Waugh et al., 2015). Our findings, however, contrast with the declining trends that have been described for both shearwater species at their breeding grounds in the Mediterranean (BirdLife International, 2018b, 2018a). Robustness in our model results was ensured by standardized long-term data collection protocols (Arroyo et al., 2014) and by a comprehensive control of those variables affecting monitoring effort and observer error during the sampling (Farmer et al., 2007; Nolte et al., 2016). Discrepancies between our trend results and previous estimates might have arisen because of the difficulty in assessing breeding population or even locating breeding sites of these secretive seabird species, since colony monitoring was limited in the past (Arcos et al., 2017). Currently there are under-surveyed areas in the Western (Defos du Rau et al., 2015) and the Eastern (Karris et al., 2017) Mediterranean where new colonies could be found. Although some fine-scale demographic studies using capture-recapture techniques have showed declines in both species (Genovart et al., 2018, 2016; Sanz-Aguilar et al., 2016), these estimates of declining trends relied on data from only a few colonies (three colonies for Scopoli's shearwater and one for Baleraric shearwater) in the Western Mediterranean. However, 8 B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740

Table 2 Model selection by AIC of the best ﬁt models predicting migration counts of shearwaters at the Strait of Gibraltar. (a) Balearic; (b) Scopoli's shearwaters. df: degrees of freedom; logLik: log likelihood.

(a)

Model df logLik AIC DeltaAIC counts ~ s(julian) þ (effort) þ (dir.W) þ (year) þ (year2)102581.841 5185.352 0 counts ~ s(julian) þ (effort) þ (dir.W) þ (year) þ (year2) þ (year:julian) 11 2581.732 5186.227 0.875 counts ~ s(julian) þ (effort) þ (dir.W) þ year 10 2600.764 5223.138 37.786 counts ~ s(julian) þ (effort) þ (dir.W) þ s(wind) þ year 10 2600.764 5223.144 37.792 counts ~ s(julian) þ (effort) þ (dir.W) þ s(cob) þ year 10 2600.761 5223.176 37.824 counts ~ s(julian) þ (effort) þ (dir.W) þ (visib) þ year 11 2600.088 5223.8 38.448 counts ~ s(julian) þ (effort) þ (dir.W) þ (prec) þ year 11 2600.417 5224.408 39.056 counts ~ s(julian) þ (effort) þ (dir.N) þ (dir.W) þ year 11 2600.428 5224.458 39.106 counts ~ s(julian) þ (effort) þ (dir.W) þ (Dis) þ year 11 2600.517 5224.62 39.268 counts ~ s(julian) þ (effort) þ (dir.W) þ s(tmin) þ year 12 2599.575 5224.832 39.48 counts ~ s(julian) þ (effort) þ (dir.N) þ (dir.W) þ (Dis) þ (prec) þ s(cob) þ s(tmin) 16 2598.064 5229.456 44.104 þ s(wind) þ (visib) þ year (b) Model df logLik AIC Delta AIC counts ~ s(julian) þ (effort) þ (prec) þ s(cob) þ s(tmin) þ s(wind) þ (visib) þ (year) þ (year2)243653.175 7354.39 0 counts ~ s(julian) þ (effort) þ (dir.N) þ (dir.W) þ (Dis) þ (prec) þ s(cob) þ s(tmin) þ s(wind) 25 3657.437 7366.297 11.907 þ (visib) þ (year) þ (year:juliana) counts ~ s(julian) þ (effort) þ (dir.W) þ (prec) þ s(tmin) þ s(wind) þ (visib) þ (year) 25 3658.223 7367.432 13.042 counts ~ s(julian) þ (effort) þ (dir.W) þ (prec) þ s(cob) þ s(tmin) þ s(wind) þ (visib) þ (year) 25 3658.22 7367.437 13.047 counts ~ s(julian) þ (effort) þ (dir.N) þ (dir.W) þ (prec) þ s(tmin) þ s(wind) þ (visib) þ (year) 26 3658.269 7369.13 14.74 counts ~ s(julian) þ (effort) þ (dir.W) þ (Dis) þ (prec) þ s(tmin) þ s(wind) þ (visib) þ (year) 26 3658.342 7369.59 15.2 counts ~ s(julian) þ (effort) þ (prec) þ s(tmin) þ s(wind) þ (visib) þ (year) 23 3661.078 7369.864 15.474 counts ~ s(julian) þ (effort) þ (dir.W) þ (prec) þ s(tmin) þ s(wind) þ (visib) 24 3660.938 7370.132 15.742 counts ~ s(julian) þ (effort) þ (dir.W) þ s(tmin) þ s(wind) þ (visib) þ (year) 24 3660.27 7370.277 15.887 counts ~ s(julian) þ (effort) þ (dir.N) þ (dir.W) þ (Dis) þ (prec) þ s(cob) þ s(tmin) þ s(wind) 27 3658.36 7371.255 16.865 þ (visib) þnbsp;(year) counts ~ s(julian) þ (effort) þ (Dis) þ (prec) þ s(cob) þ s(tmin) þ s(wind) þ (visib) þ (year) 19 3666.459 7372.221 17.831 counts ~ s(julian) þ (effort) þ (dir.N) þ (dir.W) þ (Dis) þ (prec) þ s(cob) þ s(wind) þ (visib) þ (year) 24 3666.56 7381.667 27.277 counts ~ s(julian) þ (effort) þ (dir.N) þ (dir.W) þ (Dis) þ (prec) þ s(cob) þ s(tmin) þ s(wind) þ (year) 21 3674.61 7392.349 37.959 counts ~ s(julian) þ (effort) þ (dir.N) þ (dir.W) þ (Dis) þ (prec) þ s(cob) þ s(tmin) þ (visib) þ (year) 19 3681.36 7401.353 46.963

other local breeding populations of these species within their breeding range may be following separate trajectories than those currently described. In contrast to this partial information based on a few breeding colonies, migration counts at the Strait of Gibraltar represent population trends throughout the entire breeding range of both shearwater species, integrating data from all the breeding colonies in the Mediterranean. One additional strength of sampling migration counts is that all

Table 3 Estimates from the best ﬁt GAM models predicting abundance of migrating shearwaters at the Strait of Gibraltar. (a) Balearic; (b) Scopoli's shearwaters. Data for 2005e2018.

(a)

Parametric coefﬁcients Estimate Std. Error z value Pr(>|z|) (Intercept) 79,130.00 >0.000 >8 <0.001 effort 0.299 0.050 5.987 <0.001 dir.W 0.023 0.004 6.240 <0.001 year 78.670 0.009 8352.652 <0.001 (year2) 0.020 0.000 4165.062 <0.001 Smooth terms edf Ref.df Chi.sq p-value s(julian) 5.528 9 67.36 <0.001 (b) Parametric coefﬁcients Estimate Std. Error z value Pr(>|z|) (Intercept) 4.65Eþ04 <0.000 >8 <0.001 effort 0.166 0.009 0.166 <0.001 visib 0.168 0.060 0.168 0.005 prec 0.015 0.006 0.015 0.010 year 46.260 0.011 46.260 <0.001 (year2) 0.012 <0.000 0.012 <0.001 Smooht terms edf Ref.df Chi.sq p-value s(julian) 7.548 9 476.69 <0.001 s(wind) 5.922 9 32.52 <0.001 s(tmin) 2.125 9 11.06 0.0020 B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740 9

Fig. 3. Predicted values for migrating shearwater abundance at the Strait of Gibraltar from alternative best-fit models with different regional predictors: chlorophyll concentration, sea surface temperature anomalies (SST), fisheries (data for 2005e2016) and annual trend (data for 2005e2018). (a) Balearic; (b) Scopoli's shearwaters. For Scopoli's shearwater only chlorophyll concentration and year were statistically significant (p < 0.05). individuals are recorded (juveniles and non-breeders as well as breeders), avoiding the biases occurring in population estimates derived from local breeding surveys (Arroyo et al., 2014; Weimerskirch et al., 1997). We suggest that the observed increase in migration counts could be explained by the following non-mutually exclusive causes: (1) Because of increases in survival in any age class; (2) due to an improvement of breeding success; (3) as a result of changes in the behavior of the shearwaters. 10 B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740

Table 4 Comparison of alternative best ﬁt models (data for 2005e2016). Relationship between regional predictors and abundance of Balearic shearwater is quadratic (predictor2); relationship between regional predictors and abundance of Scopoli's shearwater is linear (see Table 5). (a) Balearic shearwater; (b) Scopoli's shearwater. df: degrees of freedom. Models with Delta AIC value 2 are highlighted in grey colour).

Table 5 Parameter estimates from the alternative best-ﬁt models with different regional predictors (see Table 4). (a) Balearic; (b) Scopoli's shearwaters. Data for 2005e2016. Ref. degrees of freedom of the smooth terms in all models ¼ 9.

(a) * Parametric coefficients: mean (Std.Error) chlorophyll SST fisheries NAO effort 0.38 (0.06) 0.33 (0.05) 0.37 (0.05) 0.37 (0.05) dir.W 2.29E-02 (3.91E-03) 1.91E-02 (4.08E-03) 2.09E-02 (3.89E-03) 1.87E-02 (3.99E-03) clorophyll 48.75 (18.62) (clorophyll2) 131.3 (53.93) SST 16.57 (7.15) (SST2) 24.83 (10.86) fisheries 6.21E-05 (2.72E-06) (fisheries2) 1.40E-10 (7.30E-12) NAO 1.56 (0.64) (NAO2) 0.63 (0.31) Smooth terms: edf* s(julian) 5.1 5.19 5.31 5.22 (b) ** Parametric coefficients: mean (Std.Error) chlorophyll SST fisheries NAO effort 0.17 (0.01) 0.16 (0.01) 0.16 (0.01) 0.16 (0.01) visib 0.18 (0.07) 0.15 (0.07) 0.17 (0.07) 0.17 (0.07) prec 0.02 (0.01) 0.02 (0.01) 0.02 (0.01) 0.02 (0.01) clorophyll 4.84 (1.52) SST 0.44 (0.35) fisheries 1.77E-07 (6.29E-07) NAO 0.07 (0.08) Smooth terms: edf** julian 6.55 6.55 6.61 6.62 wind 6.42 5.91 6.14 6.17 tmin 1.87 2.02 2.12 2.02

* All the estimates are statistically significant at p-level <0.001 except for chlorophyll2, SST, SST2, NAO and NAO2 (p-level<0.05). ** All the estimates are statistically significant at p-level <0.001 except for visibility, precipitation (p-level<0.05) and NAO-index, which was not significantly related to Scopoli's abundance (p-value ¼ 0.426).

4.1. Increases in survival and/or breeding success

Numbers of migrating shearwaters contained not only adult breeders but also the non-breeding population fraction. This fraction can be great in these species (Oro et al., 2004; Peron and Gremillet, 2013). Larger numbers of migrating shearwaters could be a consequence of higher breeding success in recent years. However, if, at the same time, there are high mortality rates before reaching the maturity, most of these juvenile birds will not be recruited as adult breeders (Afan et al., 2019), thus they would not be counted at breeding sites. However, our ﬁndings suggest otherwise. Among others, different phases of migration time series within a season correspond to individuals of different age classes and populations (Panuccio et al., 2017). The increases observed in our results were consistent among all the phases of the migration time series (i.e., we did not detect any signiﬁcant interaction between day and year affecting shearwater abundance), suggesting that the increases affected all local populations and all population fractions. B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740 11

Annual survival of seabirds is high (about 90%) and with low variability, therefore impacts of food availability might be expected to be low in the survival of adult birds in these species (Cairns, 1987). However, adult survival can be strongly correlated with food availability in petrel species (Waugh et al., 2015) and fluctuations in breeding success with food supply have been widely reported for many seabirds (Cairns, 1987). Moreover, food availability, regulated through different environmental factors, explains much of the variation in both adult survival and breeding success of many seabird species (e.g., Genovart et al., 2016; Luczak et al., 2011; Tavecchia et al., 2016). Main direct effects of fisheries on the demography of seabirds involve higher mortality rates by fishing gear or by culling, while the impacts of fisheries in food availability (i.e., depletion of fish resources) also leads to indirect effects in seabird populations (Tasker et al., 2000). Specifically, longline fishing is likely the main cause of seabird mortality and possibly the most important factor contributing to the decline of some seabird populations (Dimech et al., 2009; Genovart et al., 2016; Karris et al., 2013; Laneri et al., 2010), including Balearic and Scopoli's shearwaters (Afan et al., 2019; Cortes et al., 2018; Genovart et al., 2016; Soriano-Redondo et al., 2016). However, shearwater bycatch in the Mediterranean is largely related with small-scale artisanal fisheries (e.g., Cortes et al., 2017), which presumably would have little influence on the total fishing statistics of the region. In contrast to the negative effects of fisheries, the practice of discarding unwanted fractions of commercial fish catches may benefit seabirds (e.g., Cortes et al., 2018; Genovart et al., 2016; Karris et al., 2018; Tasker et al., 2000). Indeed, breeding success, at least in Balearic shearwater, has been related to discard availability (Genovart et al., 2016). According to our models, the abundance of shearwaters increased in proportion to chlorophyll concentration and in relation to fish catches in the Mediterranean Sea. We suggest that larger food supply in recent years both of zooplankton and fish prey items, indicated in our results by chlorophyll concentration and fish catches, might have led to positive demographic consequences (i.e., increases in survival rates at all age classes and particularly higher breeding success; Genovart et al., 2016), leading to the detected increases of shearwaters in the Mediterranean.

4.2. Climate change and shearwater abundance

Previous studies have found a relationship between Scopoli's shearwater survival and breeding success with climate indexes such as NAO and SOI (Genovart et al. 2013a,b). In addition, other studies pointed out that the diet of Scopoli's shearwater can greatly differed over years in relation to surface sea temperatures (Xavier et al., 2011). Moreover, some studies also suggest a relationship between the NAO index and the Mediterranean fish stocks of small pelagic species (Tsikliras et al., 2018), which are the preferred preys of shearwaters (Louzao et al., 2015; Xavier et al., 2011). However, our results did not show a significant relationship between regional climate indexes across the Northern hemisphere (SST and NAO index) and the abundance of the migrating individuals in neither of the studied shearwater species. Mean NAO index in Western Medi- terranean Sea during the Balearic shearwater breeding season, however, seems to be positively, but not significantly, related to chlorophyll concentration in the Mediterranean and, to a lesser extent, to fish catches. Therefore, this climate index could be a regional proxy of the real factors affecting shearwater abundance in the Mediterranean, i.e., food availability (Tsikliras et al., 2018). Our results suggest that climate change would not have a great influence on the observed trends in abundance throughout the study period (i.e., lack of relationship between abundance and surface temperature anomalies). However, we must have in mind that a 10 or 14-year time frame may fall short of describing long-term climate impacts.

4.3. More shearwaters leaving the Mediterranean?

Temporal patterns of relative abundance in migrating birds are directly descriptive of corresponding patterns in populations if the proportion counted is constant through time (Dunn and Hussell, 1995; Martín et al., 2016). However, individuals of long-lived bird species have a great capacity to alter migratory behavior in response to environmental variability (e.g., Martín et al., 2014; Scholer et al., 2016). For instance, other authors have found differences in the proportion of seabirds remaining in the Bering Sea during autumn in relation to sea surface temperatures (Orben et al., 2015). We know that sea surface temperature in the Northern Hemisphere has been increasing since 1980s and it was particularly high during the last five years (Morice et al., 2012). However, according to our results, surface temperature anomalies, although related to the observed trends, explained much less variability in shearwater abundance than other environmental factors more closely related to demographic parameters (i.e. chlorophyll concentration and fish catches) in the Mediterranean Sea (Genovart et al., 2016; Soriano-Redondo et al., 2016). Moreover, findings obtained from tracked birds suggest that most of the adult Balearic shearwaters (Guilford et al., 2012) and apparently all of the Scopoli's shearwaters (Peron and Gremillet, 2013; Reyes-Gonzalez et al., 2017) migrate to the Atlantic after breeding. Only a small fraction of the total Balearic shearwater population, mainly adult birds, appeared to remain in the Mediterranean (Ruiz and Martí, 2004). Because there is lack of accurate knowledge regarding the fraction of birds remaining in the Mediterranean, we cannot entirely exclude the possibility that the observed trends might be influenced by changes in migration behavior, particularly in the case of Balearic shearwater. Other unknown factors not considered in this study (such as habitat loss and disturbance on birds, changes in inter-and intra-specific competitive relationships, among others) could also alter the number of Balearic shearwaters leaving the Mediterranean. As far as we know, the only available data on wintering population trends of Balearic shearwaters correspond to wintering birds in north-eastern Spain and western France (about 5000 and 2000 individuals respectively; Gutierrez, 2003). According to estimates of total population in 2003 (27,600 individuals; Arcos, 2011) consistent with subsequent estimates from counts of migrating birds over the Strait of Gibraltar in 2007e2010 (23,780e26,535 birds; Arroyo et al., 2014), wintering birds 12 B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740 represented about 25% of the total population estimated in 2003. However, these wintering birds showed a negative trend from early 1990s to 2002e2003, when they almost halved (Gutierrez, 2003).

4.4. Potential sources of bias in the counts

Previous studies showed that there is some dispersal of Calonectris species (C. diomedea and C. borealis) between Medi- terranean and Atlantic basins, especially from the Atlantic to the Mediterranean (Genovart et al., 2013a). However, Cory's shearwater (Calonectris borealis) have not been recorded in the Mediterranean basin except for two breeding colonies at Chafarinas Islands (about 20e30 breeding pairs) and Terreros-Almeria islet (about 10 pairs (Reyes-Gonzalez et al., 2017). Although the proportion of C. borealis has increased in Chafarinas Islands from 6% to 14% between 2000 and 2010 (Genovart et al., 2013b), apart from these breeding individuals, no other feeding or dispersal movements of Calonectris borealis have been recorded in the Mediterranean Sea (Reyes-Gonzalez et al., 2017). Our own estimates derived from the analysis of individuals depicted in photographs indicate that virtually the whole Calonectris sp. individuals recorded at the Strait of Gibraltar are Scopoli's shearwaters, supporting that the trends in abundance detected actually correspond to the species of interest in this study. On the other hand, during the non-breeding period all Balearic shearwaters remain in the northeast Atlantic (Guilford et al., 2012). However, at the end of the breeding season, Balearic shearwaters may feed along the North African shoreline (Louzao et al., 2012) in relation to food availability (Guilford et al., 2012). Birds feeding at the Strait during the migration period might lead to duplicate counts and errors in the abundance estimates, even though only birds directly ﬂying west have been considered in our study. Trends in abundance of shearwaters are associated to chlorophyll concentration in Western Mediterranean. If chlorophyll concentration patterns are related to higher feeding rates at the Strait during the migration period, duplicate counts (and therefore errors in the estimates) could also be larger. However, in contrast to the pre-breeding migration (Guilford et al., 2012), during the post-breeding migration, Balearic shearwaters tend to migrate very close to the Spanish shoreline, facilitating the detection of birds and minimizing potential sources of error in the counts (Arroyo et al., 2014; Mateos and Arroyo, 2011). In addition, in line with ﬁndings from Mateos and Arroyo (2011), our observations suggest that birds did not turn back, probably because feeding areas in the Strait are usually further to the east than the location of the observatory at Tarifa island.

4.5. Seabird population trends from migration counts

Migration monitoring has been conducted in many sites all over the world (e.g., Farmer et al., 2010; Filippi-Codaccioni et al., 2010; Martín et al., 2016; Porter and Beaman, 1985; Shamoun-Baranes et al., 2006; Verhelst et al., 2011). Sampling of birds during migration can be carried out in several different ways. For instance, counting the number of birds observed (e.g., in diurnal migration, as the counts in this study; birds observed or captured in nets during stopover; birds crossing the face of the moon; birds observed on a radar screen) or estimating the number of migrants based on flight calls as they pass through the site, among others (Dunn, 2005). Whatever the sample type is, each daily count is a sample of the birds passing over the specified count area within a 24-hr period allowing to track population change over time (Farmer et al., 2007). Migration counts can be as good as, or even better than, other sources of data currently available for trend analysis (Dunn, 2005; Farmer and Hussell, 2008). Most of the available migration monitoring focus on terrestrial birds but see Arroyo et al. (2014); Tellería (1980); http://redavesmarinas.blogspot.com/. Although migration counts have been criticized because they may reflect variation caused by weather and other factors that are not related to population change, there is a body of evidence that weather-adjusted migration counts may provide reliable population trends (Dunn et al., 1997; Dunn and Hussell, 1995; Farmer et al., 2010; Francis and Hussell, 1998; Hussell et al., 1992; Martín et al., 2016; Pyle et al., 1994). Given the lack of information regarding the changes in the population of both shearwaters in the Mediterranean at the regional scale, provided the sampling protocols and analysis applied properly address the potential sources of bias, migration counts at the Strait of Gibraltar offer a reliable source of information which can help confirm or rule out the trends derived from monitoring programmes in specific breeding areas.

4.6. Conclusions

Contrary to current estimates at breeding colonies, coastal-land based counts of migrating birds provide evidence that Baleric and Scopoli's shearwaters have been recently increasing in the Mediterranean Sea. We foresee that the growing number of shearwaters observed at the Strait should also be detected in new long-term assessments of demographic parameters at the breeding grounds. However, our results highlight that population trends in these species are complex and non-linear, suggesting that most of the increases have happened recently and intimately bounded to environmental factors that are closely related to human activities. Marine environments are inherently dynamic and food availability (indirectly modelled through chlorophyll concentration) is highly variable from one year to another. Similarly, fish catches are subjected to policy decisions that may also greatly differ in the next years. For instance, in the past years the EU Common Fisheries Policy has progressively introduced the banning of fishery discards, mainly affecting trawlery discards, imposing an obligation to land unwanted catches which may increase the bycatch mortality by longline fishery (Laneri et al., 2010) and reduce food availability. In addition, no significant improvements have been made on removing invasive species affecting shearwaters in B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740 13 the breeding sites apart from isolated initiatives throughout the Mediterranean basin. Future trends of these shearwater species in the Mediterranean may rapidly change again and decrease, as they already did, according to our results, at the beginning of the study period (up to 2010e2012). We appear to be witnessing a current increase in global population of shearwaters. However, we do not know how long this positive growth can last and which was the initial population size previous to the long-term decline observed between 1980s and 2010s (Genovart et al., 2016; present study). Recently Rodríguez et al. (2019) have highlighted the need for standardized surveys to assess population trends as one of the key priorities to fill the gap in global knowledge of petrels and shearwater species. Estimates of population size and trends derived from counts at the breeding sites for these endemic species have been demonstrated to be costly and frequently inaccurate due to the challenge that represent determining the location of the colonies and observing these secretive birds. Our study provides an example of standardized methodology to count migratory endemic shearwater species at an strategic coastal point. Our methodological approach may be complementary to breeding surveys in order to complete the overall picture of seabird species status, and provide useful estimates of the global population trend, as well as an efficient and rapid assessment of Balearic and Scopoli's shearwaters and other seabird species in the Mediterranean.

Acknowledgements

This study is part of a research project (“Environmental factors determining the interannual variation in the migration of Balearic and Scopoli's shearwaters in the Mediterranean”,2018e2019) which has been partly ﬁnanced by the Annual Pro- gramme of Grants of the Instituto de Estudios Ceutíes (IEC, Autonomous City of Ceuta, Spain), years 2018e2019. The data counts from the Strait of Gibraltar analyzed in the study were collected in ﬁeld monitoring campaigns 2003/2012 funded by grants of the Regional Ministry for the Environment of Andalusia (Spain). The Directorate-General for Coastal and Marine Sustainability of the Spanish Ministry of Agriculture, Fisheries and Food stuffs (MAPAMA) provided additional funds in the framework of the LIFE-IP-PAF INTEMARES Project (LIFE15 IPE ES 012) as a payment for technical assistance in 2017. In addition, monitoring of shearwaters has been also funded by Fundacion Biodiversidad, Spanish Ministry for the Environment (MITECO), in the framework of the MIGDATA Project (Projects for climate change adaptation, year 2017) and “Pardelas del Estrecho” Project (Projects for biodiversity conservation and environmental education, year 2018). We are grateful to the Board of the Migres Foundation. Last but not least, this study would not have been possible without the participation of hundreds of people (volunteers, collaborators and staff) who collected the information presented in this manuscript. Finally, we would like to thank three anonymous referees for providing us with comments and suggestions which greatly help to improve the manuscript.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.gecco.2019.e00740.

References

Abdellaoui, B., Falcini, F., Santoleri, J., Sammartino, M., Pisano, A., Idrissi, M., Hilm, K., 2017. Assessing the impact of temperature and chlorophyll variations on the fluctuations of sardine abundance in Al-hoceima (south Alboran sea). J. Mar. Sci. Res. Dev. 7, 1000239. Afan, I., Navarro, J., Gremillet, D., Coll, M., Forero, M., 2019. Maiden voyage into death: are fisheries affecting seabird juvenile survival during the first days at- sea? https://doi.org/10.1098/rsos.181151. Akaike, H., 1973. Nformation theory and an extension of the maximum likelihood principle. In: Petrov, B., Caski, F. (Eds.), Proceedings of the Second In- ternational Symposium on Information Theory. Akademiaiai Kiado, Budapest, pp. 267e281. Arcos, J., Oro, D., 2002. Significance of fisheries discards for a threatened Mediterranean seabird, the Balearic shearwater Puffinus mauretanicus. Mar. Ecol. Prog. Ser. 239, 209e220. Arcos, J.M., 2011. How many Balearic shearwaters are out there?: discrepancies between breeding and at sea estimates. Bol. GIAM 34, 117e122. Arcos, J., Lopez, I., Alonso, J., Mayol, J., 2017. Study, monitoring and conservation of the Balearic shearwater in Spain: an update. In: Fourth Meeting of the Population and Conservation Status Working GroupWellington, New Zealand, pp. 7e8. September 2017. New Zealand. Arroyo, G.M., Mateos-Rodríguez, M., Munoz,~ A.R., De la Cruz, A., Cuenca, D., Onrubia, A., 2014. New population estimates of a critically endangered species , the Balearic Shearwater Puffinus mauretanicus, based on coastal migration counts. Bird. Conserv. Int. 26, 87e99. https://doi.org/10.1017/ S095927091400032X. Aunins, A., Nilsson, L., Hario, M., Garthe, S., Dagys, S., Petersen, I., Skov, H., Lehikoinen, A., Mikkola-Roos, M., Ranft, S., Stipniece, A., Luigujoe, L., Kuresoo, A., Meissner, W., Korpinen, S., 2013. Abundance of waterbirds in the wintering season. In: HELCOM Core Indicator of Biodiversity. HELCOM, Helsinki, p. 25. Bartumeus, F., Giuggioli, L., Louzao, M., Bretagnolle, V., Oro, D., Levin, S.A., 2010. Fishery discards impact on seabird movement patterns at regional scales. Curr. Biol. 20, 215e222. https://doi.org/10.1016/j.cub.2009.11.073. Becker, P., Chapdelaine, G., 2003. Further development of seabird monitoring. In: Tasker, M., Furness, R. (Eds.), Seabirds Monitors of the Marine Envi- ronment. ICES Cooperative Research Report. International Council for the Exploration of the Sea No. 258, Copenhagen, Denmark, pp. 52e60. BirdLife International, 2018a. Puffinus mauretanicus. The IUCN Red List of Threatened Species 2018: e.T22728432A132658315. https://doi.org/10.2305/ IUCN.UK.2018-2.RLTS.T22728432A132658315.en. (Accessed 15 March 2019). BirdLife International, 2018b. Calonectris diomedea. The IUCN Red List of Threatened Species 2018: e.T45061132A132667885. https://doi.org/10.2305/IUCN. UK.2018-2.RLTS.T45061132A132667885.en. (Accessed 15 March 2019). Box, G.E.P., Jenkins, G.M., Reinsel, G.C., 2008. Time Series Analysis: Forecasting and Control, 4th ed. John Wiley & Sons, Upper Saddle River, NJ. Wiley Series in Probability and Statistics. Burnham, K.P., Anderson, D.R., 2002. Model selection and multimodel inference: a practical information-theoretic approach. Springer New York, New York. Cairns, D., 1987. Seabirds as indicators of marine food supplies. biolo. Oceanogr 5, 261e271. Carboneras, C., 2004. Pardela cenicienta Calonectris diomedea diomedea. In: Madrono,~ A., Gonzalez, C., Atienza, J.C. (Eds.), Libro Rojo de Las Aves de Espana.~ Direccion General para la Biodiversidad-SEO/BirdLife, Madrid, pp. 39e43. 14 B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740

Carboneras, C., Derhe, M., Ramírez, I., 2013. Update on the population status and distribution of Mediterranean shearwaters. In: (Report to Seventh Meeting of the ACAP Advisory Committee). La Rochelle, France. Cortes, V., Arcos, J.M., Gonzalez-Solís, J., 2017. Seabirds and demersal longliners in the northwestern Mediterranean: factors driving their interactions and bycatch rates. Mar. Ecol. Prog. Ser. 565, 1e16. Cortes, V., García-Barcelona, S., Gonzalez-Solís, J., 2018. Sex- and age-biased mortality of three shearwater species in longline fisheries of the Mediterranean. Mar. Ecol. Prog. Ser. 588, 229e241. Croxall, J., Rothery, P., 1991. Population regulation of seabirds: implication of their demography for conservation. In: Perrins, C., Lebreton, J.-D., Hirons, G. (Eds.), Bird Population Studies: Relevance to Conservation and Management. Oxford University Press, Oxford, UK, 272e206. Defos du Rau, P., Bourgeois, K., Thevenet, M., Ruffino, L., Dromzee, S., Ouni, R., Abiadh, A., Esteve, R., Durand, J.-P., Anselme, L., Faggio, G., Mohamed Yahya, J., Hamid, R.I., Renda, M., Miladi, B., Hamrouni, H., Alilech, S., Nefla, A., Wahbi, J., Renou, S., 2015. Reassessment of the size of the Scopoli’s Shearwater population at its main breeding site resulted in a tenfold increase: Implications for the species conservation. J. Ornithol 156, 877e892. https://doi.org/ 10.1007/s10336-015-1187-4. Derhe, M., 2012. Developing a population assessment for Scopoli's and cory's shearwaters calonectris diomedea/calonectris borealis. In: Yesou, P., Baccetti, N., Sultana, J. (Eds.), Ecology and Conservation of Mediterranean Seabirds and Other Bird Species under the Barcelona Convention e Pro- ceedings of the 13th Medmaravis Pan- Mediterranean Symposium. Alghero (Sardinia) 14-17 Oct. 2011. Medmaravis, Alghero, pp. 29e38. Diankha, O., Sow, B., Thiaw, M., Gaye, A., 2013. Seasonal variability of sea surface temperature, chlorophyll-a and Ethmalosa fimbriata abundance off the coast of Senegal. Rev. Gest. Costeira Integrada 13, 491e497. Dimech, M., Darmanin, M., Caruana, R., Raine, H., 2009. Preliminary data on seabird by-catch from the Maltese long line fishery (central Mediterranean). Collective Volume of Scientific Papers. ICCAT 64, 2335e2341. Dunn, E.H., 2005. Counting migrants to monitor bird populations: state of the art. In: Ralph, C., Rich, T. (Eds.), Proceedings of the Third International Partners in Flight Conference. Albany, CA, pp. 712e717. Dunn, E.H., Hussell, David J.T., Adams, R.J., 1997. Monitoring Songbird population change with autumn mist Netting. J. Wildl. Manag. 61, 389e396. https:// doi.org/10.2307/3802595. Dunn, E.H., Hussell, D.J.T., 1995. Using migration counts to monitor landbird populations: review and evaluation of current status. Curr. Ornithol. 12, 43e88. Dutta, S., Chanda, A., Akhand, A., Hazra, S., 2016. Correlation of phytoplankton biomass (Chlorophyll-a) and Nutrients with the catch per unit effort in the PFZ forecast areas of northern Bay of Bengal during Simultaneous validation of winter fishing season. Turk. J. Fish. Aquat. Sci. 16, 767e777. Farmer, C., Safi, K., Barber, D., Newton, I., Martell, M., Bildstein, K.L., 2010. Efficacy of migration counts for monitoring continental populations of raptors: an example using the osprey (Pandion haliaetus). Auk 127, 863e870. Farmer, C.J., Hussell, D.J.T., 2008. The Raptor Population Index in Practice 165e178. Farmer, C.J., Hussell, D.J.T., Mizrahi, D., 2007. Detecting population trends in migratory birds of prey. Auk 124, 1047e1062. https://doi.org/10.1642/0004- 8038(2007)124[1047:DPTIMB]2.0.CO;2. Filippi-Codaccioni, O., Moussus, J.-P., Urcun, J.-P., Jiguet, F., 2010. Advanced departure dates in long-distance migratory raptors. J. Ornithol. 151, 687e694. https://doi.org/10.1007/s10336-010-0500-5. Francis, C., Hussell, D.J.T., 1998. Changes in numbers of land birds counted in migration at Long Point Bird Observatory, 1961-1997. Bird. Popul. 4, 37e66. Furness, R., Becker, P., Hüppop, U., Davoren, G., 2003. Review of sensitivity of seabird populations to changes in life history parameters. In: Tasker, M., Furness, R. (Eds.), Seabirds Monitors of the Marine Environment. ICES Cooperative Research Report. International Council for the Exploration of the Sea No. 258, Copenhagen, Denmark, pp. 26e36. Genovart, M., Arcos, J.M., Alvarez, D., McMinn, M., Meier, R., Wynn, R, B., Guilford, T., Oro, D., 2016. Demography of the critically endangered Balearic shearwater: the impact of fisheries and time to extinction. J. Appl. Ecol. 53, 1158e1168. https://doi.org/10.1111/1365-2664.12622. Genovart, M., Becares, J., Igual, J.-M., Martínez-Abraín, A., Escandell, R., Sanchez, A., Rodríguez, B., Arcos, J.M., Oro, D., 2018. Differential adult survival at close seabird colonies: the importance of spatial foraging segregation and bycatch risk during the breeding season. Glob. Chang. Biol. 24, 1279e1290. https:// doi.org/10.1111/gcb.13997. Genovart, M., Sanz-Aguilar, A., Fernandez-Chac on, A., Igual, J.M., Pradel, R., Forero, M.G., Oro, D., 2013a. Contrasting effects of climatic variability on the demography of a trans-equatorial migratory seabird. J. Anim. Ecol. 82, 121e130. https://doi.org/10.1111/j.1365-2656.2012.02015.x. Genovart, M., Thibault, J.-C., Igual, J.M., Bauza-Ribot, M. del, M., Rabouam, C., Bretagnolle, V., 2013b. Population structure and dispersal patterns within and between Atlantic and Mediterranean populations of a large-range pelagic seabird. PLoS One 8 e70711ee70711. https://doi.org/10.1371/journal.pone. 0070711. Gons, H.J., Auer, M.T., Effler, S.W., 2008. MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes. Appl. Remote Sens. Monit. Freshw. Estuar. Syst. 112, 4098e4106. https://doi.org/10.1016/j.rse.2007.06.029. Gordon, A., Negrete-Yankelevich, S., Sosa, V., 2015. Ecological Statistics. Contemprorary Theory and Application. Oxford University Press, New York. Granadeiro, J.P., Monteiro, L.R., Furness, R.W., 1998. Diet and feeding ecology of Cory's shearwater Calonectris diomedea in the Azores, north-east Atlantic. Mar. Ecol. Prog. Ser. 166, 267e276. Guilford, T., Wynn, R., McMinn, M., Rodríguez, A., Fayet, A., Maurice, L., Jones, A., Meier, R., 2012. Geolocators reveal migration and pre-breeding behaviour of the critically endangered balearic shearwater Puffinus mauretanicus. PLoS One 7, 1e8. https://doi.org/10.1371/journal.pone.0033753. Gutierrez, R., 2003. The Balearic Shearwater: apparently heading for extinction. Bird. World 16, 260e263. Hashmi, D., 2000. Opportunities for monitoring seabirds and cetaceans in the Strait of Gibraltar. In: Yesou, P., Sultana, J. (Eds.), Monitoring and Conservation of Birds, Mammals and Sea Turtles in the Mediterranean and Black Seas: Proceedings of the 5th Medmaravis Symposium. Gozo, Malta, pp. 176e191. Hastie, T., Tibshirani, R., 1990. Generalized Additive Models. Chapman and Hall, New York. Hussell, D.J.T., Mather, M., Sinclair, P., 1992. Trends in numbers of tropical- and temperate-wintering migrant landbirds in migration at Long Point, Ontario, 1961-1988. In: Hagan III, J., Johnston, D. (Eds.), Ecology and Conservation of Neotropical Migrant Landbirds. Smithsonian Institution Press, Washington, DC, pp. 104e111. Hyndman, R.J., Khandakar, Y., 2008. Automatic time series forecasting: the forecast package for R. J. Stat. Softw. 1 (3), 2008. https://doi.org/10.18637/jss.v027. i03. IUCN, 2001. IUCN Red List Categories and Criteria : Version 3.1. IUCN Species Survival Commission, Gland, Switzerland and Cambridge, UK. Jovani, Roger, Grimm, Volker, 2008. Breeding synchrony in colonial birds: from local stress to global harmony. Proc. R. Soc. Biol. Sci. 275, 1557e1564. https:// doi.org/10.1098/rspb.2008.0125. Karris, G., Ketsilis-Rinis, V., Kalogeropoulou, A., Xirouchakis, S., Machias, A., Maina, I., Kavadas, S., 2018. The use of demersal trawling discards as a food source for two scavenging seabird species: a case study of an eastern Mediterranean oligotrophic marine ecosystem. Avian Res 9, 26. https://doi.org/10. 1186/s40657-018-0118-5. Karris, G., Kitsou, Z., Kalfopoulou, J., Giokas, S., Sfenthourakis, S., Poirazidis, K., 2013. Does by-catch pose a threat for the conservation of seabird populations in the southern Ionian Sea (eastern Mediterranean)? A questionnaire-based survey of local fisheries. Mediterr. Mar. Sci. 14, 19e25. Karris, G., Xirouchakis, S., Grivas, C., Voulgaris, M., Sfenthourakis, S., Giokas, S., 2017. Estimating the population size of Scopoli's Shearwaters (Calonectris diomedea) frequenting the Strofades islands (Ionian Sea, western Greece) by raft counts and surveys of breeding pairs. North West. J. Zool. 13, 101e108. Kennedy, J., Rayner, N., Smith, R., Saunby, M., Parker, D., 2011. Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850:1. Measurement and sampling uncertainties. J. Geophys. Res 116, D14103. Laneri, K., Louzao, M., Martínez-Abraín, A., Arcos, J., Belda, E., Guallart, J., Sanchez, A., Gimenez, M., Maestre, R., Oro, D., 2010. Trawling regime influences longline seabird bycatch in the Mediterranean: new insights from a small-scale fishery. Mar. Ecol. Prog. Ser. 420, 241e252. Lewis, S.A., Gould, W., 2000. Survey effort effects on power to detect trends in raptor migration counts. Wildl. Soc. Bull. 18, 317e329. B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740 15

Louzao, M., Delord, K., García, D., Boue, A., Weimerskirch, H., 2012. Protecting persistent dynamic oceanographic features: transboundary conservation efforts are needed for the critically endangered balearic shearwater. PLoS One 7, e35728. https://doi.org/10.1371/journal.pone.0035728. Louzao, M., García, D., Rodríguez, B., Abello, P., 2015. Evidence of krill in diet of balearic shearwaters Puffinus mauretanicus. Mar. Ornithol. 43, 49e51. Luczak, C., Beaugrand, G., Jaffre, M., Lenoir, S., 2011. Climate change impact on Balearic shearwater through a trophic cascade. Biol. Lett. 7, 702e705. https:// doi.org/10.1098/rsbl.2011.0225. Martín, B., Onrubia, A., de la Cruz, A., Ferrer, M., 2016. Trends of autumn counts at Iberian migration bottlenecks as a tool for monitoring continental populations of soaring birds in Europe. Biodivers. Conserv. 25, 295e309. https://doi.org/10.1007/s10531-016-1047-4. Martín, B., Onrubia, A., Ferrer, M., 2014. Effects of climate change on the migratory behavior of the common buzzard Buteo buteo. Clim. Res. 60, 187e197. Mateos, M., Arroyo, G.M., 2011. Ocean surface winds drive local-scale movements within long-distance migrations of seabirds. Mar. Biol. 158, 329e339. https://doi.org/10.1007/s00227-010-1561-y. Mateos, M., Arroyo, G.M., Rodríguez, A., Cuenca, D., De La Cruz, A., 2010. Calibration of visually estimated distances to migrating seabirds with radar measurements. J. Field Ornithol. 81, 302e309. https://doi.org/10.1111/j.1557-9263.2010.00286.x. McKnight, A., Allyn, A., Duffy, D., Irons, D., 2013. ‘Stepping stone’ pattern in Pacific Arctic tern migration reveals the importance of upwelling areas. Mar. Ecol. Prog. Ser. 491, 253e264. Morice, C., Kennedy, J., Rayner, N., Jones, P., 2012. Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: the HadCRUT4 dataset. J. Geophys. Res. 117, D08101. https://doi.org/10.1029/2011JD017187. Navarrete, J., 2008. Postbreeding migration of cory's shearwaters calonectris diomedea in Ceuta coastal waters. Bol. GIAM 31, 2e6. Nichols, J., Hines, J.E., Sauer, J.R., Fallon, F., Fallon, J., Heglund, P., 2000. A double-observer approach for estimating detection probability and abundance from point counts. Auk 117, 393e408. Nolte, E., Bart, J., Pauli, B., Kaltenecker, G.S., Heath, J.A., 2016. Detectability of migrating raptors and its effect on bias and precision of trend estimates. Avian Conserv. Ecol. 11, 9. Orben, R.A., Paredes, R., Roby, D.D., Irons, D.B., Shaffer, S.A., 2015. Wintering North Pacific black-legged kittiwakes balance spatial flexibility and consistency. Mov. Ecol. 3, 36e36. https://doi.org/10.1186/s40462-015-0059-0. Oro, D., Aguilar, J.S., Igual, J.M., Louzao, M., 2004. Modelling demography and extinction risk in the endangered Balearic shearwater. Biol. Conserv. 116, 93e102. https://doi.org/10.1016/S0006-3207(03)00180-0. Oro, D., Furness, R.W., 2002. Influences of food availability and predation on survival of kittiwakes. Ecology 83, 2516e2528. https://doi.org/10.2307/3071811. Oro, D., Louzao, M., Genovart, M., 2016. Pardela balear e Puffinus mauretanicus. In: Salvador, A., Morales, M.B. (Eds.), Enciclopedia Virtual de Los Vertebrados Espanoles.~ Museo Nacional de Ciencias Naturales, Madrid. http://www.vertebradosibericos.org. Paleczny, M., Hammill, E., Karpouzi, V., Pauly, D., 2015. Population trend of the world's monitored seabirds, 1950-2010. PLoS One 10, e0129342. https://doi. org/10.1371/journal.pone.0129342. Panuccio, M., Martín, B., Morganti, M., Onrubia, A., Ferrer, M., 2017. Long-term changes in autumn migration dates at the Strait of Gibraltar reflect population trends of soaring birds. Ibis 159, 55e65. https://doi.org/10.1111/ibi.12420. Peron, C., Gremillet, D., 2013. Tracking through life Stages: adult, immature and juvenile autumn migration in a long-lived seabird. PLoS One 8, e72713. https://doi.org/10.1371/journal.pone.0072713. Pitchaikani, J., Lipton, A., 2012. Impact of environment variables on pelagic fish landings: Special emphasis on Indian oil sardine off Tiruchendur coast, Gulf of Mannar. J. Oceanogr. Mar. Sci. 3, 56e67. Porter, R., Beaman, M., 1985. A resume of raptor migration in Europe and the Middle East. ICBP Tech. Publ. 5, 237e242. Pyle, P., Nur, N., DeSante, D., 1994. Trends in nocturnal migrant landbird populations at Southeast Farallon Island, California, 1968-1992. In: Jehl Jr., J., Johnson, N. (Eds.), A Century of Avifaunal Change in Western North America, Studies in Avian Biology, pp. 58e74. R Development Core Team, 2018. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Ramírez, F., Afan, I., Tavecchia, G., Catalan, I.A., Oro, D., Sanz-Aguilar, A., 2016. Oceanographic drivers and mistiming processes shape breeding success in a seabird. Proc. Biol. Sci. 283, 20152287, 20152287. https://doi.org/10.1098/rspb.2015.2287. Reyes-Gonzalez, J., Gonzalez-Solís, J., 2016. Pardela cenicienta - Calonectris diomedea. In: Salvador, A., Morales, M.B. (Eds.), Enciclopedia Virtual de Los Vertebrados Espanoles.~ Museo Nacional de Ciencias Naturales, Madrid. http://www.vertebradosibericos.org. Reyes-Gonzalez, J., Zaikova, Z., Morera, V., de Felipe, F., Militao,~ T., Dell'Ariccia, G., Ramos, R., Igual, J., Arcos, J., Gonzalez-Solis, J., 2017. Migracion y ecología espacial de las poblaciones espanolas~ de pardela cenicienta. Monografía no 3 del programa Migra. SEO/BirdLife, Madrid. Rodríguez, A., Arcos, J.M., Bretagnolle, V., Dias, M.P., Holmes, N.D., Louzao, M., Provencher, J., Raine, A.F., Ramírez, F., Rodríguez, B., Ronconi, R.A., Taylor, R.S., Bonnaud, E., Borrelle, S.B., Cortes, V., Descamps, S., Friesen, V.L., Genovart, M., Hedd, A., Hodum, P., Humphries, G.R.W., Le Corre, M., Lebarbenchon, C., Martin, R., Melvin, E.F., Montevecchi, W.A., Pinet, P., Pollet, I.L., Ramos, R., Russell, J.C., Ryan, P.G., Sanz-Aguilar, A., Spatz, D.R., Travers, M., Votier, S.C., Wanless, R.M., Woehler, E., Chiaradia, A., 2019. Future directions in conservation research on petrels and shearwaters. Front. Mar. Sci. 6, 94. https://doi. org/10.3389/fmars.2019.00094. Rubolini, D., Møller, A., Rainio, K., Lehikoinen, E., 2007. Intraspecific consistency and geographic variability in temporal trends of spring migration phenology among European bird species. Clim. Res. 35, 135e146. Ruiz, A., Martí, R., 2004. La Pardela Balear. SEO/BirdLife-Conselleria de Medi Ambient del Govern de les Illes Balears, Madrid, Spain. Sanz-Aguilar, A., Igual, J., Tavecchia, G., Genovart, M., Oro, D., 2016. When immigration mask threats: the rescue effect of a Scopoli's shearwater colony in the Western Mediterranean as a case study. Biol. Conserv. 198, 33e36. Scholer, M.N., Martín, B., Ferrer, M., Onrubia, A., Bechard, M.J., Kaltenecker, G.S., Carlisle, J.D., 2016. Variable shifts in the autumn migration phenology of soaring birds in southern Spain. Ardea 104, 83e93. https://doi.org/10.5253/arde.v104i1.a. Shamoun-Baranes, J., Van Loon, E., Alon, D., Alpert, P., Yom-Tov, Y., Leshem, Y., 2006. Is there a connection between weather at departure sites, onsetof migration and timing of soaring-bird autumn migration in Israel? Glob. Ecol. Biogeogr. 15, 541e552. https://doi.org/10.1111/j.1466-8238.2006.00261.x. Soriano-Redondo, A., Cortes, V., Reyes-Gonzalez, J.M., Guallar, S., Becares, J., Rodríguez, B., Arcos, J.M., Gonzalez-Solís, J., 2016. Relative abundance and distribution of fisheries influence risk of seabird bycatch. Sci. Rep. 6, 37373. Tasker, M.L., Camphuysen, C.J., Cooper, J., Garthe, S., Montevecchi, W.A., Blaber, S.J.M., 2000. The impacts of fishing on marine birds. ICES J. Mar. Sci. 57, 531e547. https://doi.org/10.1006/jmsc.2000.0714. Tavecchia, G., Tenan, S., Pradel, R., Igual, J.-M., Genovart, M., Oro, D., 2016. Climate-driven vital rates do not always mean climate-driven population. Glob. Chang. Biol. 22, 3960e3966. https://doi.org/10.1111/gcb.13330. Tellería, J., 1980. Autumn migration of cory's shearwater through the Straits of Gibraltar. Bird Study 27, 21e26. Tellería, J.L., 1981. La migracion de las aves en el estrecho de Gibraltar. Volumen II: Aves no planeadoras. Universidad Complutense, Madrid. Tsikliras, A.C., Licandro, P., Pardalou, A., McQuinn, I.H., Groger,€ J.P., Alheit, J., 2018. Synchronization of Mediterranean pelagic fish populations with the North Atlantic climate variability. Deep-Sea Res. Part II Top. Stud. Oceanogr. https://doi.org/10.1016/j.dsr2.2018.07.005. Vegv ari, Z., Bokony, V., Barta, Z., Kovacs, G., 2010. Life history predicts advancement of avian spring migration in response to climate change. Glob. Chang. Biol. 16, 1e11. https://doi.org/10.1111/j.1365-2486.2009.01876.x. Verhelst, B., Jansen, J., Vansteelant, W., 2011. South West Georgia: an important bottleneck for raptor migration during autumn. Ardea 99, 137e146. Waugh, S.M., Barbraud, C., Adams, L., Freeman, A.N.D., Wilson, K.-J., Wood, G., Landers, T.J., Baker, G.B., 2015. Modeling the demography and population dynamics of a subtropical seabird, and the influence of environmental factors. Condor Ornithol. Appl. 117, 147e164. https://doi.org/10.1650/CONDOR- 14-141.1. Weimerskirch, H., Brothers, N., Jouventin, P., 1997. Population dynamics of wandering albatross Diomedea exulans and Amsterdam albatross D. amsterda- mensis in the Indian Ocean and their relationships with long-line fisheries: conservation implications. Biol. Conserv. 79, 257e270. 16 B. Martín et al. / Global Ecology and Conservation 20 (2019) e00740

Wood, S.N., 2011. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Ser. Soc. B Stat. Methodol. 73, 3e36. https://doi.org/10.1111/j.1467-9868.2010.00749.x. Wynn, R.B., Josey, S., Martin, A., Johns, D., Yesou, P., 2007. Climate-driven range expansion of a critically endangered top predator in northeast Atlantic waters. Biol. Lett. 3, 529e532. https://doi.org/10.1098/rsbl.2007.0162. Xavier, J.C., Magalhaes,~ M.C., Mendonç, A.S., Antunes, M., Carvalho, N., Machete, M., Santos, R.S., Paiva, V., Hamer, K.C., 2011. Changes in diet of cory's shearwaters calonectris diomedea breeding in the azores. Mar. Ornithol. 39, 129e134. https://doi.org/10.3354/meps166267. Zacharias, M.A., Roff, J.C., 2001. Use of focal species in marine conservation and management: a review and critique. Aquat. Conserv. Mar. Freshw. Ecosyst. 11, 59e76. https://doi.org/10.1002/aqc.429.