Dr Inga Lips

Urmas Lips

Keywords: coastal upwelling, nutrients, phytoplankton, Gulf of Finland, Baltic Sea Coastal upwelling, nutrients, phytoplankton, Gulf of Finland, Baltic Sea

d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

Phytoplankton growth in the sea is primarily controlled by nutrient availability and solar radiation. The generation time of phytoplankton is mostly one to a few days during nonsexual reproduction, which could result in a time scale of a day to a few weeks for a noticeable change in phytoplankton biomass.

Species specific nutrient requirements are important factors in regulating the phytoplankton community and will lead to modifications in the community structure when nutrient availability changes [START_REF] Sommer | The role of competition of recources in phytoplankton succession[END_REF]. Phytoplankton distribution in coastal waters, e.g. Baltic Sea, varies over small distances (less than 10 km) and short time scales (few days). Such changes are strongly associated with local changes in nutrient concentrations in the euphotic zone. The key to understand local changes observed in phytoplankton dynamics in coastal waters lies in explaining the possible mechanisms of nutrient supply to the euphotic zone.

The summer period in the Baltic Sea area is characterized by the development of a strong seasonal thermocline. This strong stratification prevents mixing between the nutrient depleted upper layer and the nutrient rich lower layers. Wind-induced vertical mixing [START_REF] Lilover | Late summer vertical nutrient fluxes estimated from direct turbulence measurements: a Gulf of Finland case study[END_REF] and upwelling [START_REF] Zhurbas | Modeling of the mesoscale structure of coupled upwelling/downwelling events and related input of nutrients to the upper mixed layer in the Gulf of Finland, Baltic Sea[END_REF] are the important processes in bringing nutrient-rich waters from deeper layers to the surface at this time of year. The speed of biological response to high nutrients and light is taxonspecific and may also be influenced by initial macro-nutrient concentrations/ratio (i.e. ''shift-up'' dynamics described by [START_REF] Dugdale | Realization of new production in coastal upwelling areas: a means to compare relative performance[END_REF] and the presence of micronutrients [START_REF] Hutchins | An iron limitation mosaic in the California upwelling regime[END_REF].

While the nutrient ratios in oceanic water are close to Redfield [START_REF] Tyrell | The relative influences of nitrogen and phosphorus on oceanic primary production[END_REF], adjacent seas like the Baltic Sea deviate strongly from this ratio showing large regional and seasonal differences [START_REF] Danielsson | Alterations in nutrient limitations -Scenarios of a changing Baltic Sea[END_REF]. Baltic Sea deep water and summer sub-thermocline water have characteristically low dissolved inorganic nitrogen to dissolved inorganic phosphorus (DIN:DIP) ratios due to the widespread internal loading of phosphate [START_REF] Pitkänen | Internal nutrient fluxes counteract decreases in external load: the case of the estuarial eastern Gulf of Finland, Baltic Sea[END_REF][START_REF] Carstensen | Coastal eutrophication and trend reversal: A Danish case study[END_REF]. Based on a low DIN:DIP ratio in the upwelling water, the filamentous nitrogen-fixing cyanobacteria would be expected to outcompete other phytoplankton species but as shown in previous studies [START_REF] Kanoshina | The influence of weather conditions (temperature and wind) on cyanobacterial bloom development in the Gulf of Finland (Baltic Sea)[END_REF][START_REF] Vahtera | Effect of upwelling on the pelagic environment and bloom-forming cyanobacteria in the western Gulf of Finland, Baltic Sea[END_REF] upwelled waters have too low temperatures for cyanobacteria to benefit from the upward transported nutrients and due to the wind-forced Ekman transport the cyanobacteria filaments in the upper layer will be advected away from the upwelling region. At the same time coastal upwelling in the Baltic Sea has been shown to stimulate the growth of other phytoplankton and also phototrophic ciliate species during upwelling events [START_REF] Heiskanen | Contamination of sediment trap fluxes by vertically migrating phototrophic micro-organisms in the coastal Baltic Sea[END_REF][START_REF] Kanoshina | The influence of weather conditions (temperature and wind) on cyanobacterial bloom development in the Gulf of Finland (Baltic Sea)[END_REF][START_REF] Kononen | Development of a deep chlorophyll maximum of Heterocapsa triquetra Ehrenb. at the entrance to the Gulf of Finland[END_REF][START_REF] Kręŝel | Influence of coastal upwelling on chlorophyll a concentration in the surface water along the Polish coast of the Baltic Sea[END_REF][START_REF] Vahtera | Effect of upwelling on the pelagic environment and bloom-forming cyanobacteria in the western Gulf of Finland, Baltic Sea[END_REF]. The typical life span of upwelling ranges from 0.5 to 10 days in the Baltic Sea [START_REF] Bychkova | Use of satellite data for identification and classification of upwelling in the Baltic Sea[END_REF]. Nutrient concentration may be changed on a time scale of a few days and could result in transient consequences for growth, fluctuations in biomass, and competition between phytoplankton species. The objective of this paper is to describe phytoplankton distribution and analyse changes in community structure influenced by several consecutive coastal upwelling events in the Gulf of Finland in July-August 2006. Such extensive hydrophysical, chemical and biological (including phytoplankton community data) data collected before, during and after several coastal upwelling events has seldom been analysed previously in order to link changes in phytoplankton community with changes in hydrophysical and the chemical environment in the Baltic Sea.

METHOD

Study area and sampling

Mapping of hydrographic, chemical and biological fields was carried out in the central part of the Gulf of Finland (Fig. 1) in July-August 2006 (11 July, 19-20 July, 25 July, 8 August, 15-16 August, 22 August and 29 August). The southernmost sampling station TH1 was located < 2 km off the coast in the Tallinn Bay and the northernmost station TH27 about 5 km from the archipelago area off Helsinki.

The width of the gulf in the study area is < 80 km. The water depths are 25-40 m in the inner Tallinn Bay followed by a steep bottom sloping to about 90 m in the southern part of the open gulf and a general northward shallowing with remarkable irregularities of the sea bed. Vertical profiles of temperature, salinity and chlorophyll a fluorescence were recorded at 27 stations (distance between stations 2.6 km) and water samples for inorganic nutrient (PO 4 3 ¯, NO 2 ¯+NO 3 ¯), chlorophyll a and phytoplankton analyses were collected at 14 stations (except on 19-20 July when sampling was made only at the northernmost stations TH19-27; distance between stations 5.2 km) from the upper mixed layer. Water samples for nutrient analyses were collected also from the seasonal thermocline with a vertical resolution of 2.5-5.0 metres.

Chemical and biological analyses

Measurements were carried out using a NBIS Mark III CTD (conductivity, temperature, depth) probe and an SBE 19 CTD probe (Sea-Bird) equipped with a WETStar fluorimeter (WET Labs). The salinity values were calculated using algorithms from Fofonoff and Millard Jr. (1983) and are presented without units. Salinity data were quality checked against the water sample analyses by a high precise salinometer AUTOSAL (Guildline). A rosette sampler with 8 Niskin water samplers (volume 1.7 l) was used for sampling. To represent the upper mixed layer (UML), the samples were prepared by pooling three (in case of a shallow UML -two) samples taken from the surface layer from the 1-m depth down to the seasonal thermocline, the depth of which was determined from the CTD casts.

Nutrient analyses were carried out according to the guidelines of the American Public Health Association (APHA, 1992; methods 4500-NO3 F and 4500-P F) and analysed using an automatic nutrient analyzer µMac 1000 (Systea S.r.l.). The lower detection range for phosphate-phosphorus and nitrate+nitrite-nitrogen was 1 ppb (parts per billion; 0.03 µM and 0.07 µM, respectively; with a measurement uncertainty of 20% near the detection limit). Samples for phosphates (PO 4 3 ¯) were mostly analysed immediately onboard after sampling and samples for dissolved inorganic nitrogen compounds (NO 3 ¯+NO 2 ¯) determination were deep-frozen after collection and analysed later in the on-shore laboratory.

The chlorophyll a (Chl a) content from UML (pooled sample prepared as described above) was determined on Millipore APFF glass-fibre filters following the extraction at room temperature in the dark with 96% ethanol for 24 hours. Chlorophyll a content from the extract was measured spectrophotometrically (Thermo Helios γ; photometric accuracy: ±0.005A at 1A) in the laboratory [START_REF] Helcom | Guidelines for the Baltic Monitoring Programme for the third stage[END_REF].

Phytoplankton sub-samples (100 ml) were preserved with acid Lugol solution and analysed using the [START_REF] Utermöhl | Zur Vervollkommnung der quantitativen Phytoplanktonmetodic[END_REF] technique and PhytoWin software by Kahma Ky. Cyanobacterial filaments were counted as 100-µm segments and other phytoplankton species as single cells or colonies. All biomass data are given as wet weight.

Data analysis

Statistical analysis was performed using the PRIMER 6.0 software (PRIMER-E Ltd) with user guidelines (Clarke and Warwick, 2001). in the surface layer of the Gulf of Finland (Fig. 2 ). Three upwelling events occurred and were mapped during the study period. A relatively weak upwelling was present near the northern coast on 19-20

July. A major upwelling event developed near the southern coast in the first half of August and was mapped on 8 August and 15-16 August. The next upwelling event near the southern coast, which appeared in late August, was sampled on 29 August.

The upwelling event near the northern coast caused a drop in temperature in the UML at the two northernmost stations from 19-20 °C to 14-17 °C on 19 July but no changes in the UML salinity were observed (Fig. 3a,b). On the basis of water sample analyses, only PO 4 3 ¯concentrations in the UML slightly exceeded the lower detection range at some stations on 19 July, but it is not clear whether this could be attributed to the upwelling event or not (Fig. 3c,d).

Wind-induced northward drift of surface waters and development of an upwelling in the beginning of August along the southern coast brought cold and saltier waters with high amounts of inorganic nutrients into the surface layer (Fig. 3a-d At the beginning of study on 11 July 2006, phytoplankton Chl a and biomass distribution (Fig. 3e,f) in the UML were patchy along the cross-section between Tallinn and Helsinki in the Gulf of Finland. The Chl a concentrations varied between 3.4 and 7.1 mg m -3 and the total wet weight phytoplankton biomass ranged between 580 and 2050 mg m -3 . A comparison of Chl a and biomass values revealed some discrepancies in their horizontal distributions on 11 July, especially at station TH17 where a local minimum of Chl a (4.8 mg m -3 ) coincided with a local maximum of total biomass (1920 mg m -3 ). On 19 July, an upwelling event, which developed in the northern part of the cross-section, influenced Chl a and phytoplankton biomass values in the UML. Against a background of a relatively low phytoplankton Chl a and biomass level in the northern part of the study area, higher values were measured at station TH25, which could be regarded as the upwelling front (see Fig. 3a). However, a significant maximum of total biomass (1820 mg m -3 ) was associated with a relatively moderate maximum of Chl a (5.1 mg m -3 ). A more uniform distribution of phytoplankton Chl a and biomass with lower values in the southern part and higher values in the central and northern part of the study transect was observed on 25 July. The Chl a and biomass distributions were well correlated, the values varied between 3.9 and 6.4 mg m -3 , and 480 and 1380 mg m -3 , respectively.

A clear decline in Chl a concentration and phytoplankton biomass in the Tallinn Bay and a sharp increase in the northern part of the cross-section were observed on 8 August. The decrease of Chl a The last upwelling event at the end of August also had a significant impact on the Chl a (decrease from 5.0 to 2.7 mg m -3 ) and the total phytoplankton biomass (decrease from 800 mg m -3 to 480 mg m -3 ) and distribution in the upwelling area in the Tallinn Bay. At the same time both the Chl a and biomass decreased also on the rest of the study transect (but the decrease was less pronounced), where, on average, the Chl a concentration decreased from 4.7 to 3.6 mg m -3 and total biomass from 620 to 450 mg m -3 .

Dynamics of phytoplankton species and community structure

July

The dynamics of horizontal distribution of some phytoplankton key species are shown in 78-83 mg m -3 corresponding to over 2.4 x 10 6 cells L -1 ). Among nanoflagellates high biomass values were also contributed by prasinophytes, Pyramimonas spp. Schmarda, especially at stations TH7, TH11, TH23 and TH25 (>100 mg m -3 ; >12% of total wet weight biomass). and Aphanizomenon sp. (11%). In comparison with the biomass values measured a week before, the following changes were observed: H. triquetra biomass increased from 169 mg m -3 to 368 mg m -3 , M.

rubra from 6 mg m -3 to 265 mg m -3 , D. acuminata from 0 mg m -3 to 111 mg m -3 and Aphanizomenon sp. biomass decreased from 157 mg m -3 to 110 mg m -3 . At station TH25 the biomass of H. triquetra was about three times higher than that at station TH27 and more than a half of total wet weight biomass was formed by this species (1013 mg m -3 ; 56%). The second dominant species at station TH25 was Aphanizomenon sp. (368 mg m -3 ; 22%). Among small flagellates Eutreptiella spp. de Cunha dominated but the biomass was low (22-24 mg m -3 ; 25-35% of total nanoplankton wet weight biomass).

On 25 July phytoplankton biomass was gradually increasing towards the north along the cross-section.

Higher biomass values at stations TH25-TH27 (1284-1381 mg m -3 ) were dominated by H. triquetra, Aphanizomenon sp. and Nodularia spumigena Mertens (324-542 mg m -3 , 25-39 %; 292-339 mg m -3 , 21-26 % and 130-211 mg m -3 , 9-16 % respectively). At the other stations N. spumigena was detected in significant amounts only at station TH3 (~300 mg m -3 ; 31%) and H. triquetra had higher biomass also at stations TH11-TH23 (260-440 mg m -3 ; 24-41%). Among nanoflagellates Chrysochromulina spp. had higher biomass at stations TH17-TH21 (36-43 mg m -3 ; 3.4-4 % of total wet weight biomass)

and Pyramimonas spp. in a wider open gulf area at stations TH15-TH23 (64-137 mg m -3 ; 6-13 %)

August

The development of upwelling near the southern coast of the gulf in the beginning of August had a dramatic influence not only on the distribution pattern of temperature, salinity and nutrients (Fig. 3 a-d; 8 August) but also on the phytoplankton Chl a and total biomass distribution (Fig. 3e,f) and community structure (Fig. 4) along the entire cross-section. On 8 August the surface waters at stations TH1-TH7, previously dominated by filamentous cyanobacteria and the dinoflagellate H. triquetra (54-78 % and 8-20 % of total wet weight biomass respectively), were dominated by the photosynthetic ciliate M. triquetra had high (yet lower than that observed in July) biomass value only at station TH25 contributing with 18 % to the total wet weight biomass. Among small flagellates very high biomass was formed by Pyramimonas spp. at stations TH23 and TH25 (230-480 mg m -3 ; 10-20 % of total wet weight biomass; Fig. 4). The biomass of the latter species increased between the two surveys from 56 mg m -3 to 356 mg m -3 .

By 15-16 August the upwelling area had widened off shore (Fig. 3a-d biomass from 64 mg m -3 to 98 mg m -3 and from 33 mg m -3 to 90 mg m -3 respectively. Additionally, small flagellates Chrysochromulina spp. (1.4-11 % of total wet weight biomass) and cryptomonads (3.7-7 %) appeared in the community in a considerable amount. The increase in biomass, on average, from 6 mg m -3 to 22 mg m -3 and from 16 mg m -3 to 26 mg m -3 respectively, was measured. The highest biomass of M. rubra (446 mg m -3 , 55 %) was measured at station TH13 in the upwelling front. In less saline waters, which appeared at the northern end of the study transect (stations TH21-TH27, Fig. 3b), the communities were dominated by filamentous and colonial cyanobacteria species (72-88 %).

After the change in wind direction from mainly easterly winds to south-westerly winds in the period contributed 3-10 % to the total wet weight biomass (decrease from 90 mg m -3 to 6 mg m -3 on average).

Prymnesiophytes Chrysochromulina spp. and cryptomonads had slightly decreased in biomass (contributing 3-7.5 % and 2-4 % of total wet weight biomass respectively).

The development of the next upwelling event along the southern coast of Gulf of Finland, which was sampled on 29 August, changed the phytoplankton community structure in the area affected by the upwelling again. The ciliate M. rubra slightly increased in biomass compared with the previous week (Fig. 4) and contributed 18-53 % of total wet weight biomass. Similarly to the previous upwelling event Pyramimonas spp. had a considerable share in the total wet weight biomass (12-26 %) at stations TH1-TH5. At the same time Pseudopedinella spp. did not show any increase in biomass during this upwelling event (Fig. 4). Instead, the contribution of H. triquetra and heterotrophic naked dinoflagellates to the total wet weight biomass slightly increased (5-21 % and 3-19 % respectively at stations TH1-TH7), although the biomass of H. triquetra stayed relatively low (110 mg m -3 ). The contribution of Aphanizomenon sp. to the total wet weight biomass was very small at the near shore station but gradually increased off shore (Fig. 4). The biomass of cryptophytes and Chrysochromulina spp. (Fig. 4) was low in the area affected by the upwelling on 29 August.

MDS analysis

Multi-dimensional scaling (MDS) analysis of similarities in the community structure at all stations during the entire study period clearly categorized the phytoplankton composition into several distinguishable clusters. Area 1 in Figure 5 includes stations before the upwelling event on 11 and 25

July and those which were not affected by the major upwelling on 8 August (23c-27c in Fig. 5). The same community structure was revealed on 19-20 July, except that at station TH27 (marked as 27x in Fig. 5). Thus, the phytoplankton community was relatively stable in the area in July and the high biomass community observed on 8 August in the northern part of the study transect matches with the July community. The stations sampled during the major upwelling event in the southern part of the study transect were grouped in area 2 (1c-7c and 1d-11d). Station TH1 was not placed at the same point in different weeks as the bigger share of Chrysochromulina spp. and cryptomonads was found in the southernmost part of the upwelling area on 15-16 August compared with the communities on 8 August. Area 3 includes the stations from the central part of the study area (9c-21c) sampled on 8 August where the phytoplankton community clearly differed from both the July community and the upwelling water community.

Dissimilar communities to all those described above were observed on 15-16 August in the areas outside the upwelling waters whereas the community in the upwelling front (13d) was closer to the upwelling community than to the communities outside the upwelling area.

MDS analysis shows strong similarity in the community structure at stations TH1-TH9 (1e-9e) on 22

August with the community structure sampled on 8 August at stations TH9-TH21 (9c-21c; area 3 in Fig. 5). The phytoplankton community at station TH13 (13e) on 22 August matches the same group while the community in a colder water patch at station TH11 (11e) was slightly different. The communities at the rest of stations on 22 August were close to the community observed at stations TH21-TH27 (21d-27d) a week earlier. Area 4 includes the stations sampled in the upwelling area on 29 August. Those communities differed from the ones observed during the previous upwelling event in the same area. The communities in the northern half of the study transect, which stayed outside the upwelling influence on 29 August, diverged from the previously observed communities as well. [START_REF] Patti | Factors responsible for the differences in satellite-based chlorophyll a concentration between the major global upwelling areas[END_REF] have suggested that in the major coastal ocean upwelling regions several driving factors, such as nutrient concentration, light availability, shelf extension and a surface turbulence proxy must be taken into account when investigating the phytoplankton biomass distribution. Wind-driven transport and mixing play three key roles in shelf productivity: nutrient supply to the euphotic zone, light control through vertical mixing of primary producers, and offshore export of near surface plankton, However, while the first process yields a strong positive biological response to upwelling winds, the other two influences lead to negative productivity responses to increased wind (Largier et al., 2006). During the coastal upwelling events in the Baltic Sea, the distribution of phytoplankton biomass and production have been found to be strongly influenced by the combined effects of physicochemical processes and to be related to the strength of wind and hence upwelling events (Kononen and , 1986;[START_REF] Vahtera | Effect of upwelling on the pelagic environment and bloom-forming cyanobacteria in the western Gulf of Finland, Baltic Sea[END_REF][START_REF] Zalewski | Primary production and chlorophyll a concentration during upwelling events along the Hel Peninsula (the Baltic Sea)[END_REF][START_REF] Nausch | Phosphorus input by upwelling in the eastern Gotland Basin (Baltic Sea) in summer and its effects on filamentous cyanobacteria[END_REF]. In the Gulf of Finland there is a strong upwelling-downwelling coupling because of the elongated shape and relatively short distance (48-135 km) between northern and southern coasts. The development of upwelling along the southern coast of Gulf of Finland in the first half of August 2006 had a strong influence on the spatial distribution of phytoplankton biomass/species (Fig. 3f and4) and community structure (Fig. 5) along the entire cross-section between Tallinn and Helsinki. In general, a strong biomass decrease in the area affected by the major upwelling event and an increase of biomass near the opposite coast was observed, and there was strong evidence of negative and positive effects of this event on different phytoplankton species.

DISCUSSION

In plankton community studies very often phytoplankton are divided into several size-classes. At low nutrient levels phytoplankton species succession usually proceeds towards small and motile species with high surface to volume ratios, which give an advantage in nutrient uptake (e.g. [START_REF] Kiørboe | Turbulence, phytoplankton cell size, and the structure of pelagic food webs[END_REF]. In ocean upwelling systems larger and especially diatom species are considered to dominate the phytoplankton community (e.g. [START_REF] Lassiter | Phytoplankton assemblages in the CoOP-WEST coastal upwelling area[END_REF][START_REF] Anabalón | The contribution of nanoand micro-planktonic assemblages in the surface layer (0-30 m) under different hydrographic conditions in the upwelling area off Concepción, central Chile[END_REF]. In contrast to the general understanding and expectations, in our observations the smaller phytoplankton size fraction showed a faster response to the upwelled nutrients compared with the larger size fraction. It was shown by [START_REF] Kuvaldina | The influence of a coastal upwelling event to the spatio-temporal distribution of nutrients and chlorophyll a in the Gulf of Finland, Baltic Sea: observational results[END_REF] that a clear increase in Chl a mostly in <20 µm size class occurred during the stabilisation phase of the upwelling (sampled on 15-16 August 2006) while an increase of Chl a in larger size fraction was observed after the upwelling relaxation on 22 August. [START_REF] Stolte | Effect of nitrogen source on the size distribution within marine phytoplankton populations[END_REF] described how larger phytoplankton cells can only become dominant when NO 3 ¯ is the major nitrogen source available and NH 4 + is low or at detection levels, as is typically seen in oceanic coastal upwelling ecosystems. [START_REF] Koike | Inorganic nitrogen metabolism by Antarctic phytoplankton with special reference to ammonium cycling[END_REF] found that on average only 50% of the NO 3 ¯ uptake is by organisms in the <20µm size fraction, while all the NH 4 + uptake ocurred the same fraction. According to the Finnish marine monitoring data (http://www.itameriportaali.fi/en/tietoa/helcom_seuranta/en_GB/bmp_data) the NH 4 + concentrations in the lower layers of the Gulf of Finland where the upwelling water originates were comparable to the nitrates+nitrites concentrations in July-August 2006. The median and mean values being 1.6 and 1.8 µM, respectively, between the 30 metres depth and the sea bed. High NH 4 + concentrations in the upwelling waters have been also measured earlier in the Gulf of Finland, e.g. up to 1.43 µM by Haapala (1994) in summer and up to 3.2 µM by [START_REF] Lignell | Beyond bulk properties: Responses of coastal summer plankton communities to nutrient enrichment in the northern Baltic Sea[END_REF] in autumn whereas in the later case the nitrate concentrations up to 2.2 µM were observed. Thus, we suggest that the phytoplankton growth observed in the upwelling area, initially mostly in the smaller size fraction ), could be related to the possible higher proportion of ammonium in the upwelled dissolved inorganic nitrogen pool.

As shown by the previous studies in the Gulf of Finland [START_REF] Kanoshina | The influence of weather conditions (temperature and wind) on cyanobacterial bloom development in the Gulf of Finland (Baltic Sea)[END_REF][START_REF] Vahtera | Effect of upwelling on the pelagic environment and bloom-forming cyanobacteria in the western Gulf of Finland, Baltic Sea[END_REF] the growth of Eutreptiella gymnastica Throndsen, Chrysochromulina spp. and cryptophyceans has been influenced by the coastal upwelling events. During our study Eutreptiella spp. dominated among nanoflagellates (25-35% of total nanoplankton wet weight biomass) only on 19 July in the upwelling area at the northernmost part (stations TH25-TH27) of the cross-section but the biomass values were very low. There was no biomass increase observed in connection to the major upwelling event along the southern coast in August. Chrysophytes Pseudopedinella spp. were abundant only during the major upwelling event near the southern coast and their increased biomass values were limited with the upwelling time and area except for slightly increased biomass near the northern coast on 8 August (Fig. 4). Pyramimonas spp. were also positively influenced by the major upwelling event in August near the southern coast of the Gulf of Finland although the highest biomass was observed on 8 August in the northern part of the study transect. Chrysochromulina spp. had highest biomass on 11 July and a decrease in biomass was observed during the initiation phase of the upwelling while a consecutive increase in biomass followed during the stabilisation phase and the biomass stayed relatively high also after the relaxation of upwelling.

Mesocosm studies [START_REF] Uitto | Grazing by mesozooplankton and metazoan microplankton on nanophytoplankton in a mesocosm experiment in the northern Baltic[END_REF][START_REF] Lagus | Species-specific differences in phytoplankton responses to N and P enrichments and the N:P ratio in the Archipelago Sea, northern Baltic Sea[END_REF][START_REF] Kangro | Species-specific responses of a cyanobacteria-dominated phytoplankton community to artificial nutrient limitation in the Baltic Sea[END_REF] have shown that Pseudopedinella spp. have high growth rates in high nutrient enrichment conditions and the other experiments [START_REF] Kononen | Physiological and community responses of summer plankton to nutrient manipulation in the Gulf of Finland (Baltic Sea) with special reference to phosphorus[END_REF][START_REF] Andersson | Changes in the pelagic microbial food web due to artificial eutrophication[END_REF] have also revealed the positive response of Pyramimonas spp. to nutrient enrichment following the sharp decline caused by predation of increased microzooplankton community. Thus, these species have a high requirement for nutrients, and hence might have a competitive advantage during upwelling events which explains the increase in their biomass in the major upwelling area in our study. As shown by studies of [START_REF] Hajdu | Seasonal dynamics of Chrysochromulina species (Prymnesiophyceae) in a coastal area and a nutrient-enriched inlet of the Northern Baltic Proper[END_REF] Among larger size fraction the biomass of the photosynthetic ciliate M. rubra increased remarkably during the upwelling event and remained at high values till the end of August almost along the entire cross-section. The biomass increase of latter species during the upwelling event was first connected with the vertical transport of seed population from lower layers followed by growth in the nitrate rich upwelled waters in the euphotic layer. The former conclusion is supported by sampling on 11 July at stations TH1-TH3 where in the lower part of thermocline (17.5-20 m) biomass of this species of up to 246 mg m -3 was measured. High biomass values and even blooms of M. rubra have been observed in upwelling areas (e.g. review by Crawford, 1989). The species has been shown to have a high demand for inorganic nitrogen, but also one to four times higher uptake rate for nitrate than e.g. diatoms or dinoflagellates [START_REF] Wilkerson | Formation of blooms by the symbiotic ciliate Mesodinium rubrum: the significance of nitrogen uptake[END_REF]. The latter helps also explain the rapid exhaustion of inorganic nitrogen compounds in M. rubra dominated upwelling areas. The competitive advantage during nutrient limitation is retained probably by changing the trophic status from phototrophy to phagotrophy (e.g. [START_REF] Yih | Ingestion of cryptophyte cells by the marine photosynthetic ciliate Mesodinium rubrum[END_REF] and by the species' very high swimming speed (e.g. [START_REF] Lindholm | Mesodinium rubrum -a unique photosynthetic ciliate[END_REF][START_REF] Villarino | Evidence of in situ diel vertical migration of a red-tide microplankton species in Ria de Vigo (NW Spain)[END_REF], which allows it to exploit resources from deeper water layers as well as from nutrient patches.

A H. triquetra bloom has been detected in the upwelling area in the Gulf of Finland in 1998 [START_REF] Kanoshina | The influence of weather conditions (temperature and wind) on cyanobacterial bloom development in the Gulf of Finland (Baltic Sea)[END_REF] when the biomass values reached as high as 4 500 mg m -3 . During our study in 2006 the biomass of this species was high (up to 1 040 mg m -3 ) mostly only in July in the northern part of the Gulf of Finland. High biomass values did not extend to the Tallinn Bay and no remarkable biomass increase was found during and after the major upwelling event near the southern coast where biomass only up to 100 mg m -3 was measured. We noticed that the highest H. triquetra biomass values observed at station TH17 on 11 July and at station TH25 on 19 July were associated with relatively low Chl a concentrations. Kononen et al. (1999) have shown that at low irradiances Chl a concentration in a pure culture of H. triquetra decreased rapidly while the cells could maintain their in vivo fluorescence for a week. Since the Chl a fluorescence in the UML at these stations was remarkably high (data not shown here), we suggest that H. triquetra was transported there from the seasonal thermocline. This suggestion is supported by the CTD data from 19 July showing that the isopycnal, which surfaced in It could be explained by the fact that the upwelled water during the major event near the southern coast had its origin from much deeper layers than that during the earlier upwelling in the northern part. It was estimated by [START_REF] Lips | Consequences of coastal upwelling events on physical and chemical patterns in the central Gulf of Finland (Baltic Sea)[END_REF] that the upwelling water on 8 August consisted of a mixture of waters from below the thermocline and from the UML with a share of 85 % and 15 % while the higher temperatures observed in the upwelling water on 19 July indicate that this water mass had its origin mainly from the seasonal thermocline.

There was a clear increase in phytoplankton Chl a and biomass after the relaxation of the major upwelling sampled on 22 August (Fig. 3e,f). However, the highest total phytoplankton biomass was observed on 8 August in the northern part of the study transect. Even the observed major upwelling event brought large amount of inorganic nutrients to the nutrient depleted UML it can be seen from the nutrient analyses that nitrates+nitrites were below the lower detection range already by 15-16 August and phosphates by 22 August (Fig. 3c,d). In contrast, the phosphate concentrations exceeding the lower detection range were observed in the UML in the northern part of the study transect on 25 July and 8

August. Due to our sampling strategy we could not point to a direct link between the upwelling observed on 19-20 July and the slightly elevated phosphate content observed in the northern gulf on 25

July and 8 August. We rather relate the elevated phosphate content and high phytoplankton biomass to the meso-scale features observed at the mentioned sampling days. Especially, a clear relationship was evident on 8 August, when according to the vertical distributions of temperature, salinity and density [START_REF] Lips | Consequences of coastal upwelling events on physical and chemical patterns in the central Gulf of Finland (Baltic Sea)[END_REF]), anti-cyclonic like vertical distribution of isopycnals was observed in the downwelling area coupled with the major upwelling. TH25 coincided with this meso-scale feature where domed isopycnals caused shallowing of the UML to only 5 metres against the background of relatively deep UML in the rest of the downwelling area.

Earlier modelling and field experiments have shown that regardless of how much nutrient is upwelled during the upwelling phase, if a suitable period of relaxation follows, all is taken up within 72 h = 3 days [START_REF] Zimmerman | Acceleration of nutrient uptake by phytoplankton in a coastal upwelling ecosystem: a modeling analysis[END_REF][START_REF] Dugdale | Realization of new production in coastal upwelling areas: a means to compare relative performance[END_REF] and high levels of primary productivity are found in 3 to 7 day old upwelled waters after the relaxation following the upwelling impulse [START_REF] Botsford | Effects of variable winds on biological productivity on continental shelves in coastal upwelling systems[END_REF][START_REF] Wilkerson | The phytoplankton bloom response to wind events and upwelled nutrients during the CoOP-WEST Study[END_REF] in the ocean upwelling systems. When upwelling relaxes and the supply of new nutrients decreases/disappears, phytoplankton populations may survive by using intracellular storages or regenerated forms of nutrients such as ammonium and urea (e.g. [START_REF] Bode | Nitrate storage by phytoplankton in a coastal upwelling environment[END_REF]. As the nitrates+nitrites were exhausted rapidly and there was still plenty of phosphates in the UML on 15-16 August (Fig. 3d) one could hypothesize that the depletion of the latter nutrient and the increase of biomass of filamentous N 2 -fixing cyanobacteria Aphanizomenon sp. and Anabaena sp. (Fig. 4) observed on 22 August could be due to the growth induced by upwelled excess dissolved inorganic phosphorus (DIP). However, the results of MDS analysis indicated very high similarity of phytoplankton community in the area previously affected by the upwelling (stations TH1-TH13, except station TH11) on 22 August to the community found in the central part of our cross-section during the intensive upwelling event on 8 August (Fig. 5). Thus, the phytoplankton biomass increase could be connected to the relaxation of upwelling and subsequent reversal movement of surface water masses together with the utilization of mostly regenerated but also stored nutrients. While, because of a long time for bloom development, the phytoplankton community may be lost from the system and moved quite far in oceanic upwelling areas (e.g. [START_REF] Botsford | Effects of variable winds on biological productivity on continental shelves in coastal upwelling systems[END_REF], in the case of variable windinduced upwelling in the elongated Gulf of Finland, plankton community may not move far before being brought back again. The absence of cyanobacteria dominated community described on our study transect on 15-16 August and possibly some other changes observed in the community structure could be related to the along-shore (along the gulf axis) advection, which has been shown to be very important in coastal upwelling systems, e.g. in the California Current System [START_REF] Botsford | Effects of variable winds on biological productivity on continental shelves in coastal upwelling systems[END_REF].

The development of a next upwelling event by 29 August caused a decrease in phytoplankton biomass and the observed changes in the community composition support the above described importance of wind-induced Ekman transport in shaping the overall response of phytoplankton to the coastal upwelling events in the Gulf of Finland ecosystem. The response of the phytoplankton community to several consecutive upwelling events in the same area is not similar and is most probably influenced by the amount and ratio of upwelled nutrients, but also by the strength of the upwelling that determines from which layers the upwelled water originates from and consequently what is the initial community structure in the upwelling area.

Conclusions

During the upwelling events in the Baltic Sea transport of large amounts of inorganic nutrients from the lower layers to the surface layer may occur. Due to the nutrient intrusion, changes in temperature, advection and replacement/mixing of water masses not only single phytoplankton species are affected but also the entire phytoplankton communities are changed in a short time period. The response of different phytoplankton species/size classes tends to be very much influenced by the concentration/ratio of upwelled nutrients also by the strength of the upwelling events that determines the water layers where the upwelling water originates from. In general we found that the increase of biomass takes much longer time than the observed abrupt changes in the phytoplankton community caused by upwelling or horizontal advection (convergence/divergence) of water masses. Thus, one should be careful in using the collected and analysed chemical and phytoplankton data for assessing the status of the Gulf of Finland ecosystem due to the very dynamic nature of this estuary and the background information (climatic conditions, prevailing hydrophysical processes) have to be considered for this purpose.

  from 4.2 to 1.8 mg m -3 and total biomass from 950 to 290 mg m -3 at the southern end of the study transect was related to the low phytoplankton biomass in the cold upwelled water. The highest Chl a (14.3 mg m -3 ) and biomass (2320 mg m -3 ) values were measured at stations TH23 and TH25 in the area, which could be regarded as an area of the horizontal convergence of surface waters due to the northward Ekman drift in the UML.The decrease in inorganic nutrient concentrations coincided with an increase in Chl a and phytoplankton biomass values during the stabilization and relaxation phases of the observed upwelling (Fig.3e,f; 15-16 and 22 August respectively). The average phytoplankton Chl a and biomass values at the four southernmost sampling stations (TH1, TH3, TH5, TH7) occupied by the upwelling event on 8 August increased from 1.8 mg m -3 and 290 mg m -3 to 3.8 mg m -3 and 600 mg m -3 by 15-16 August and to 5.0 mg m -3 and 800 mg m -3 by 22 August. At the same time the phytoplankton Chl a and biomass decreased at the northernmost part of the study transect from the observed maximum values on 8 August to 6.6 mg m -3 and 750 mg m -3 by 15-16 August and to 5.4 mg m -3 and 720 mg m -3 by 22 the sampling stations in the open gulf (TH9-TH21) the temporal variability of Chl a and phytoplankton biomass in the period from 8 August to 22 August was not as high as that described above in relation to the southernmost and northernmost parts of the study transect. However, a local maximum of phytoplankton biomass of 820 mg m -3 at station TH13 on 15 August and a local minimum of biomass of 470 mg m -3 at station TH11 on 22 August was noted. The maximum was related to the upwelling front (seeFig. 3a,b;[15][16] and the minimum to a slightly colder and saltier surface water patch (Fig.3a,b; 22 August).

  Figure 4. At the beginning of the study (11 July) the distribution of phytoplankton species in the UML did not show any distinguishable pattern. Phytoplankton wet weight biomass (Fig. 3f) was patchy along the sampled cross-section and filamentous cyanobacteria species/groups were dominating in the community (Aphanizomenon sp. (L.) Ralfs, Prochlorothrix Burger-Wiersma, Stall et Mur, 1989/Pseudanabaena Lauterborn group and Anabaena (Bory) spp.), except at station TH17 where the dinoflagellate Heterocapsa triquetra (Ehrenberg) Stein was dominant (1039 mg m -3 ; 54% of total wet weight biomass). Very high abundances of Chrysochromulina spp. Lackey were recorded on 11 July when maximum biomass values of these species were measured at stations TH7, TH13 and TH15 (Fig. 4;

in

  rubra (23-42 %) and small-sized flagellates Pyramimonas spp. and Pseudopedinella spp.N. Carter 1937 (19-30 % and 8-17 % respectively). The decrease in filamentous cyanobacteria biomass at stations TH1-TH7 in comparison with that measured before the development of upwelling was, on average, from 76 mg m -3 to 5 mg m -3 and in dinoflagellate H. triquetra biomass from 101 mg m -3 to 8 mg m -3 . The increase in Pyramimonas spp. biomass was, on average, from 47 mg m -3 to 64 mg m -3 and Pseudopedinella spp. biomass from 10 mg m -3 to 33 mg m -3 in the same area. M. rubra increased in biomass from 2 mg m -3 to 97 mg m -3 . Very high biomass communities in the northern part of the crosssection at stations TH23-TH25 were dominated by filamentous cyanobacteria Aphanizomenon sp. (23-26 %), Anabaena spp. (15-22 %) and Prochlorothrix/Pseudanabaena group (9-18 %). The increase in biomass, if compared with that measured on 25 July in the same area, was as it follows: from 250 mg m -3 to 566 mg m -3 in Aphanizomenon sp., from 48 mg m -3 to 384 mg m -3 in Anabaena spp. and from 102 mg m -3 to 401 mg m -3 in Prochlorothrix/Pseudanabaena group biomass. Dinoflagellate H.

  ) and at the same time an increase in Chl a and phytoplankton biomass were detected (Fig.3e-f). Even the total biomass values in the area affected by upwelling (stations TH1-TH11) had increased, the community was still dominated by M. rubra (25-47 %) and small-sized flagellates Pyramimonas spp. and Pseudopedinella spp.(11-23 % and 11-26 % respectively). M. rubra biomass increased in comparison with the previous week, on average, from 97 mg m -3 to 168 mg m -3 , and Pyramimonas spp. and Pseudopedinella spp.

  from 16-20 August, the relaxation of upwelling occurred by 22 August and the phytoplankton community structure in the sea area previously affected by upwelling changed. M. rubra was still one of the dominants (12-28%) in this region but the other dominants were N 2 -fixing filamentous cyanobacteria Aphanizomenon sp. (14-43 %) and Anabaena spp. (6-16 %). In comparison with the -16 August, the increase, on average, from 7 mg m -3 to 205 mg m -3 in Aphanizomenon sp. and from 4 mg m -3 to 59 mg m -3 in Anabaena spp. biomass was measured at stations TH1-TH11. At the southernmost station TH1 10 % of total wet weight biomass was formed by H. triquetra. Small flagellates dominating during the upwelling event had decreased in biomass. Chrysophytes Pseudopedinella spp. had almost disappeared from the community. Prasinophytes Pyramimonas spp.

(

  Pyramimonas spp. and Pseudopedinella spp.

  stronger stratification may be one of the factors influencing Chrysochromulina spp. abundance positively during summer to early autumn in the Baltic Sea. New input of limiting nutrients during the upwelling event at the beginning of August together with the stabilisation of upwelling and rise of the UML temperature (leading to development of stratification) might have caused the Chrysochromulina spp. biomass increase in the Estonian coastal waters observed on 15-16 August. Also phosphorus deficiency in the UML gives a competitive advantage through toxin production[START_REF] Estep | Taxonomy, life-cycle, distribution and dasmotrophy of Chrysochromulina: a theory accounting for scales, haptonema, muciferous bodies and toxicity[END_REF]) and hence the high abundances at periods with low phosphate concentrations (e.g. along our study transect in July 2006, Fig.4).

  (station TH25), was located at 12 m depth at a distance of 5 km towards the open gulf (station TH23).[START_REF] Vahtera | Effect of upwelling on the pelagic environment and bloom-forming cyanobacteria in the western Gulf of Finland, Baltic Sea[END_REF] found relatively high biomass of Aphanizomenon sp. in the upwelling front in the northern part of the Gulf of Finland in 1998 and they explained this by the displacement of populations of Aphanizomenon sp., which before the upwelling event resided in the thermocline. We observed similarly relatively high biomass of Aphanizomenon sp. biomass in the upwelling front on 19 July in the northern part of the gulf. However, the biomass of Aphanizomenon sp. was negligible during the major upwelling event sampled on 8 and 15-16 August near the southern coast also on 11 July the biomass of this species up to 1300 mg m -3 was measured at stations TH1-TH3 at 12.5 m depth (upper part of the thermocline; at the same time its biomass did not exceed 150 mg m -3 at 15 m depth and below).

Figure 1 .

 1 Figure legends

Figure 2 .

 2 Figure 2. Eastward wind stress (dashed line) in July-August 2006 estimated using wind data from

Figure 3 .

 3 Figure 3. Temporal changes of temperature (a, ºC), salinity (b), nitrate+nitrite-nitrogen (c, µM), phosphate-phosphorus (d, µM), chlorophyll a concentration (e, mg m -3 ) and phytoplankton biomass (f, mg m -3 ) in the UML along the study transect from 11 July to 29 August 2006. Dots indicate

Figure 4 .

 4 Figure 4. Temporal change of biomass of different phytoplankton species in the UML along the study

Figure 5 .

 5 Figure 5. MDS plot for all sampled stations based on Bray-Curtis similarity distances of phytoplankton

6 RESULTS Upwelling events and related temperature, salinity and nutrient dynamics

	According to the wind stress estimates southward cross-gulf Ekman drift prevailed in July and
	northward cross-gulf Ekman drift prevailed in August 2006 (with an exception from 15 to 20 August)
	F o
	r
	P
	e e r
	R e v i e w
	To compare the community structure at different sampling
	stations on different sampling days the ordination of samples by multi-dimensional scaling (MDS) was
	performed. Biomass of all species at all stations was used for Bray-Curtis similarity coefficient
	(transformed by square root) calculations.

Horizontal distribution of phytoplankton Chl a and biomass

	F o
	r
	P
	e e r
	; 8 August). The concentrations as high as 0.48 µM of 3 ¯ were measured in the upwelling area. A widening of the upwelling area and a drop of nitrates+nitrites concentrations below the lower detection range and a decrease of NO 3 ¯+NO 2 ¯ and 0.79 µM of PO 4 PO 4 3 ¯ concentrations in the upwelling water within a week between surveys on 8 and 15-16 August (Fig. 3c,d) was observed. After the relaxation of the upwelling an increase of sea surface temperature R e v i e w
	was observed and the UML water was depleted of inorganic nutrients (22 August). The formation of
	next upwelling, which was sampled on 29 August, caused a drop of sea surface temperature from 15-
	16 °C to 10-12 °C and an increase in salinity from 4.8 to 5.6, although it did not bring detectable
	amounts of nitrates+nitrites into the UML but only amounts of phosphates compared with the previous
	upwelling event.
	7

  The highest biomass values at stations TH23 and

	F o
	r
	P
	e e r
	R e v i e w
	17

http://mc.manuscriptcentral.com/jplankt Journal of Plankton Research

ACKNOWLEDGEMENTS

Authors appreciate the help of colleagues and crew members who participated at the field measurements in the frame of this study. We thank the Finnish Meteorological Institute for providing us with wind data at Kalbådagrund station and the Finnish Environment Institute (former Finnish Institute of Marine Research) for access to their marine monitoring data.

FUNDING

This work was financially supported by the Estonian Science Foundation (grant no. 6752) and Foundation Innove (grant no. 1.0101-0279). Page 18 of 28 http://mc.manuscriptcentral.com/jplankt Journal of Plankton Research


Luis Cadahía

Pascual López-López
email: pascual.lopez@uv.es

Vicente Urios

Juan José Negro

C Gortázar

Satellite telemetry reveals individual variation in juvenile Bonelli's eagle dispersal areas

Keywords: Aquila fasciata, Conservation, Dispersal, Hieraaetus fasciatus, Management, PTT, Raptors, Remote sensing

Natal dispersal is the time elapsed between departing from the natal site and settling to attempt breeding for the first time. In long-lived species with deferred sexual maturity this period may last several years, making this process crucial for their survival and conservation. Here we present a large-scale outline of juvenile Bonelli's eagle's dispersal areas in the Iberian Peninsula. We describe the ranging and movement patterns of 14 juvenile Bonelli's eagles during their dispersal period, studied by satellite telemetry. Three distinct phases during the juveniles' first year of life were detected, namely, the dependence period, the departure from the parental territory, and the settlement in dispersal areas. In general, between-sex differences in relation to ranging behavior were not significant. Interestingly, there seems not to be a few, clearly delimited, overlapping Bonelli's eagle's juvenile dispersal areas within the Iberian Peninsula. A total of 17 dispersal areas were detected, with some animals using more than one. These areas were located in eight autonomous communities (Spanish administrative units), being the most important Castilla-La Mancha and Andalucía. Juveniles were more frequently located in cultivated man-managed areas, with non-irrigated herbaceous crops. This is probably due to higher prey availability and higher efficiency in prey capture in these open areas, as well as to the absence of breeding pairs. This has important management implications, suggesting that conservation efforts should focus on the whole landscape matrix of manmanaged ecosystems rather than in a few clearly delimited geographic areas.

Introduction

Dispersal is an ecological process with important implications in spatial population structure, survival, and gene flow among populations (Clobert et al. 2001;Bullock et al. 2002), hence affecting persistence, evolution, and conservation of species (Clobert et al. 2001;Bullock et al. 2002). The ecological and evolutionary aspects of dispersal are directly linked with the processes of 'natal dispersal' (movement between the birthplace and the first breeding site) and 'breeding dispersal' (movement between successive breeding sites; [START_REF] Greenwood | The natal and breeding dispersal of birds[END_REF], which are the ones that involve flow of individuals and genes among different areas and populations. The time elapsed between departure from the natal site and settling to attempt breeding for the first time may last several years in longlived species with deferred sexual maturity. This makes the fate of dispersing individuals during this time crucial, since whether or not animals complete successfully the natal dispersal period and transmit their genes to the next generation will importantly affect the maintenance of the species in the long-term.

Bonelli's eagle Aquila fasciata (Accipitridae, Falconiformes) reaches sexual maturity at 3-4 years [START_REF] Cramp | Handbook of the birds of Europe, the Middle East and North Africa[END_REF]. This bird of prey is catalogued as "Least Concern" in Europe (BirdLife International 2009) and as "Endangered" in Spain (Real 2004), where the main fraction of the population from the Western Palaearctic dwells. Studying dispersal in this species has been traditionally difficult, basically owing to the long movements that juveniles perform. Studies have relied on the use of rings and wing-tags [START_REF] Cheylan | Dispersion des Aigles de Bonelli Hieraaetus fasciatus juveniles bagués en France[END_REF]Real and Mañosa 2001;[START_REF] Hernández-Matías | Determinants of territorial recruitment in Bonelli's Eagle (Aquila fasciata) populations[END_REF] or conventional radio-tracking (Balbontín and Ferrer 2009). However, there is no clear picture of where juveniles from different areas of the distribution range stay during their juvenile dispersal period until they are recruited into the breeding population.

Bonelli's eagle nestlings fledge at an approximate age of 60 days [START_REF] Real | Post-nestling dependence period in the Bonelli's eagle Hieraaetus fasciatus[END_REF][START_REF] Mínguez | Factors influencing length of the post-fledging period and timing of dispersal in Bonelli's eagle (Hieraaetus fasciatus) in Southwestern Spain[END_REF]) and spend several weeks in the nest surroundings until they leave the parental territory [START_REF] Real | Post-nestling dependence period in the Bonelli's eagle Hieraaetus fasciatus[END_REF][START_REF] Mínguez | Factors influencing length of the post-fledging period and timing of dispersal in Bonelli's eagle (Hieraaetus fasciatus) in Southwestern Spain[END_REF]Balbontín 2003;[START_REF] Cadahía | Survival and movements of satellite-tracked Bonelli's Eagles Hieraaetus fasciatus during their first winter[END_REF][START_REF] Cadahía | Bonelli's Eagle Hieraaetus fasciatus juvenile dispersal: hourly and daily movements tracked by GPS[END_REF]. Previous studies based on direct observations and radio-tracking data have shown that juvenile Bonelli's eagles perform long-distance movements and settle in the so-called dispersal areas. These areas are characterized by high prey abundance, mainly rabbits and pigeons, where juveniles settle during long-time periods before recruitment into the breeding population, sometimes shared with juveniles of other raptor species such as Golden eagle Aquila chrysaetos and Spanish Imperial eagle Aquila adalberti [START_REF] Cheylan | Dispersion des Aigles de Bonelli Hieraaetus fasciatus juveniles bagués en France[END_REF]Real and Mañosa 2001;Balbontín 2003;[START_REF] Cadahía | Survival and movements of satellite-tracked Bonelli's Eagles Hieraaetus fasciatus during their first winter[END_REF]Cadahía et al. , 2007;;Balbontín and Ferrer 2009;Moleón et al. 2009a). However, dispersal areas hold several threats that directly affect birds' survival, mainly direct persecution, bird electrocution in dangerous poles of power lines, and poisoning in extensive game reserves (Real et al. 2001;Real 2004;[START_REF] Cadahía | Survival and movements of satellite-tracked Bonelli's Eagles Hieraaetus fasciatus during their first winter[END_REF]. This has become especially important after the rabbit viral hemorrhagic disease and myxomatosis outbreaks, which have lead to the confinement of Bonelli's eagle to areas with a relatively high level of human influence, hence increasing juvenile's mortality risk (Moleón et al 2009a). For this reason, the accurate delineation of these areas is of paramount importance in order to establish adequate management actions aimed at ensuring the long-term persistence of the species in Spain.

Herein we describe the movement and ranging patterns of 14 Bonelli's eagles during juvenile dispersal in Spain, using continuous, long-term satellite tracking data. The main goals of this work are to explore the distancing pattern from the natal areas, and to outline and describe the dispersal areas, discussing the implications for the conservation of this endangered species.

Methods

Between 2002 and 2004, we tagged 14 Bonelli's eagle juveniles, 12 nestlings and two recent fledglings, with satellite transmitters (hereafter PTTs-platform transmitter terminals) in eastern Spain (autonomous communities of Catalonia, Valencian Community, and Murcia, encompassing a latitudinal range between 41°18′05′′ N to 37°36′26′′ N; Fig. 1). All nests were located in rocky cliffs, except for one on a pine tree, surrounded by Mediterranean scrubland. All birds were weighed, measured, and fitted with PTTs using a Teflon harness [START_REF] Kenward | A manual for wildlife radio tagging[END_REF]. Birds' gender was established by molecular techniques using a blood sample [START_REF] Fridolfsson | A simple and universal method for molecular sexing of non-ratite birds[END_REF].

Three types of PTTs were used: five 30-g battery powered Argos/PTT-100s, seven 35-g solar powered Argos/PTT-100s, and two 45-g Argos/GPS PTT-100s, manufactured by Microwave Telemetry, Inc. (www.micro wavetelemetry.com). Combined Argos/GPS transmitters permit birds to be tracked by the Argos and the GPS systems simultaneously, whereas for the other transmitters information was provided by the Argos system. Transmitters were set to an 8-h on/120-h off duty cycle, except for the two Argos/GPS PTTs, which were set to 16-h on/ 72-h off. Transmitter weight never exceeded 3% of the birds' body mass (2.1±0.5% SD; n=14; range, 1.3-3.0%), as recommended by [START_REF] Kenward | A manual for wildlife radio tagging[END_REF]. To determine best time for tagging (ca. 50 days old), nestlings' age was estimated based on feather and plumage pattern using a spotting telescope [START_REF]Efecto de la altitud y de la disponibilidad de presas en la fecha de puesta del águila-azor perdicera (Hieraaetus fasciatus) en la provincia de Granada (SE de España)[END_REF]. When actually handling the birds, we estimated age more precisely as age=0.200×tail length (mm)+16.262 [START_REF] Mañosa | Age estimation and growth patterns in nestling Bonelli's eagles[END_REF].

Locations' initial management was made by Argos, a satellite-based location reception and data collection system. A satellites network collects PTTs' data and relays them to ground processing stations [START_REF] Gortázar | Movements of juvenile Bonelli's Eagles Aquila fasciata during dispersal[END_REF]. Argos/ PTTs positions are computed based on measuring the Doppler shift (for a detailed description see [START_REF] Kenward | A manual for wildlife radio tagging[END_REF][START_REF] Gortázar | Movements of juvenile Bonelli's Eagles Aquila fasciata during dispersal[END_REF]. This system provides seven location classes (LCs) that reflect the nominal accuracy of each data. These LCs are necessary because several factors, either intrinsic or external to the PTT, may affect locations accuracy (thoroughly discussed in [START_REF] Kenward | A manual for wildlife radio tagging[END_REF][START_REF] Soutullo | Accuracy of lightweight satellite telemetry: a case study in the Iberian Peninsula[END_REF][START_REF] Gortázar | Movements of juvenile Bonelli's Eagles Aquila fasciata during dispersal[END_REF]. In this study, we used LCs 3, 2, and 1, with nominal accuracy <250, 250-500, and 500-1,500 m, respectively [START_REF] Gortázar | Movements of juvenile Bonelli's Eagles Aquila fasciata during dispersal[END_REF]. We also included locations of lower quality (LC 0, A, and B), but filtered them using available information on eagles' movements, based on comparisons with high-quality GPS data and on Argos accuracy tests [START_REF] Cadahía | Bonelli's Eagle Hieraaetus fasciatus juvenile dispersal: hourly and daily movements tracked by GPS[END_REF][START_REF] Soutullo | Accuracy of lightweight satellite telemetry: a case study in the Iberian Peninsula[END_REF]. To avoid bias connected with spatial and temporal autocorrelation, we computed the harmonic means of all the locations collected on each given day [START_REF] Dixon | Harmonic mean measure of animal activity areas[END_REF][START_REF] Kenward | A manual for wildlife radio tagging[END_REF]) and used them for subsequent calculations.

The onset of dispersal was considered to occur when birds flew beyond the average inter-nest distance (11.4 km) and did not return within that distance in the following two locations, as described in [START_REF] Cadahía | Estimating the onset of dispersal in endangered Bonelli's eagle Hieraaetus fasciatus tracked by satellite telemetry: a comparison among methods[END_REF]. To study the distancing pattern at the onset of dispersal, the first year of life was divided into 30-day long months and monthly distance to natal nest was computed as the mean of all distances within a given month [START_REF] Soutullo | Post-fledging behaviour in Golden eagles Aquila chrysaetos: onset of juvenile dispersal and progressive distancing from the nest[END_REF]. For each bird, we recorded date and age at the onset of dispersal and estimated home ranges using kernel contours [START_REF] Worton | Kernel methods for estimating the utilization distribution in home-range studies[END_REF][START_REF] Kenward | A manual for wildlife radio tagging[END_REF] optimized by a least square cross validation procedure [START_REF] Kenward | A manual for wildlife radio tagging[END_REF][START_REF] Kenward | Density and linkage estimators of home range: nearest-neighbour clustering defines multinuclear cores[END_REF]. We considered as total area the surface enclosed within a 95% kernel of the whole-transmitting-period collected locations. Dispersal areas' size was estimated with the 'Animal Movement SA v 2.04' extension for ArcView 3.2 [START_REF] Hooge | Animal movement extension to ArcView[END_REF]. For dispersal areas estimation, we used a 25% kernel computed after departure from natal areas. We used this figure in particular because hourly and daily distances covered within and outside the so estimated areas were observed to be significantly different [START_REF] Cadahía | Bonelli's Eagle Hieraaetus fasciatus juvenile dispersal: hourly and daily movements tracked by GPS[END_REF], enabling distinction between exploratory movements and settlements in dispersal areas [START_REF] Ferrer | The Spanish imperial Eagle[END_REF]. In those individuals with more than one dispersal area, we considered the pooled size of all of them for calculations. We computed the gravity center of dispersal areas as the harmonic mean of all the locations contained within each area [START_REF] Dixon | Harmonic mean measure of animal activity areas[END_REF][START_REF] Kenward | Density and linkage estimators of home range: nearest-neighbour clustering defines multinuclear cores[END_REF] and measured the distance between this point and the natal nest in each case. In birds with more than one dispersal area, we estimated this distance using the area where they stayed longer. The number of autonomous communities (Spanish administrative units) with part of their territory within a dispersal area was also registered.

We used a Kruskal-Wallis test to search for differences among monthly distances to natal nests during the first year of life and a Games-Howell test [START_REF] Zar | Biostatistical analysis[END_REF] to perform monthly pairwise comparisons. The Mann-Whitney test was used to test between-sex differences in date and age at dispersal, differences in maximum distance reached during the whole transmitting period, size of total ranges and number, and size and distance to natal nests of dispersal areas.

To explore whether juveniles spent more time in certain types of habitat than expected by chance, the Global Landcover Map 2000 [START_REF] Pekel | The land cover map for Europe in the year 2000[END_REF]) was used to roughly characterize dispersal area in terms of soil coverage. This GIS coverage includes 18 different habitat types, varying from forests, scrublands, cultivated areas, wetlands, grasslands, water bodies, and urban areas (for a detailed description see [START_REF] Pekel | The land cover map for Europe in the year 2000[END_REF]. We used the 'Animal Movement SA v 2.04' extension to select 50 points randomly distributed within the dispersal areas and then the 'Get grid value' extension to assign a land-use class both to these random points and to the telemetry locations. We only used the highest quality location classes (LC 3, 2, and 1) for this analysis. To search for between-individuals differences in the habitat of their dispersal areas, we compared the frequency of random points in each type of coverage using contingency tables (Soutullo et al. 2008b). To find out whether birds preferably selected particular habitat types (within-individuals differences), we compared the frequency of each type of coverage in each group of points, i.e., locations and random points, using a χ 2 test for each individual. All statistical analyses were performed with SPSS ver. 13.0. Significance level was established at p<0.05.

Results

Birds were tracked during the period 2002-2006 (Table 1). The end of transmission occurred during the dispersal stage in all birds but one, which was recruited into the breeding population when it was 4 years old [START_REF] Cadahía | Natal dispersal and recruitment of two Bonelli's eagles Aquila fasciata: a fouryear satellite tracking study[END_REF]. In relation to sex, females tended to disperse younger (age at dispersal: Mann-Whitney, U=4.000, Z=-2.160, p=0.034) but not earlier than males (dispersal date: Mann-Whitney, U=12.000, Z=-0.926, p=0.414; Fig. 2,Table 2). Monthly distance varied throughout the first year of life (Kruskal-Wallis, H=58.308, df=9, p<0.001). Three distinct phases were observed (Games-Howell, p>0.069 in groups of similar months): an initial stage of restricted movements around the nest during the third and fourth months of life (the "dependence period"), followed by a rapid increase in distance to the nest (including the "onset of dispersal"), and a settling from the seventh month onwards. The onset of dispersal, that happened suddenly and in short time, occurred between the fifth and sixth month in females and in the sixth month in males (Fig. 2).

Considering the whole transmitting period, maximum distance to natal nests ranged between 90 and 663 km (after excluding birds no. 6, 8, and 12 for which only a few locations after the onset of dispersal were recorded) and did not differ between sexes (Mann-Whitney, U=17.500, Z= -0.077, p=0.940), similar to the total range size covered by juveniles (Mann-Whitney, U=8.000, Z=-1.543, p=0.148; Table 2). Dispersal areas' size and their distance to natal nests did not differ between sexes either (size: Mann-Whitney, U= 7.000, Z=-1.697, p=0.106; distance: Mann-Whitney, U= 17.000, Z=-0.154, p=0.940; Table 2). Dispersal areas encompassed land from eight autonomous communities, mainly Castilla-La Mancha and Andalucía (Fig. 1, Table 1). Interestingly, only birds 7 and 11 overlapped their dispersal areas, at least partially, while the others remained geographically separated (Fig. 1).

Overall, ten land-use classes were present in the dispersal areas, and significant differences were found among juveniles regarding the habitat composition of these areas (χ 90 2 =65.336, p=0.002). In most of them, the habitat class "cultivated and managed areas with non-irrigated herbaceous crops" was most abundant, whereas others showed a more heterogeneous mixture of habitats. By individual, in all birds but two (bird 4: χ 4 2 =11.649, p= 0.02; bird 9: χ 8 2 =180.506, p<0.001), there were no differences between the frequency of satellite locations in the assortment of land-use classes and the proportion of these habitats observed within the dispersal areas (remaining individuals p>0.115). Thus, juveniles were found more frequently in the most abundant type of habitat, i.e., "cultivated and managed areas, with non-irrigated herbaceous crops", and, secondarily, in "cultivated and managed areas with irrigated herbaceous crops" and in "closed scrubland". The two birds with significant differences were also found more frequently in these two types of land-use classes, although their dispersal areas showed a more heterogeneous habitat. In fact, no differences among individuals were found regarding the frequency of locations in the different land-use classes within their dispersal areas (χ 90 2 =39.949, p=0.158).

Discussion

The juvenile dispersal period has remained one of the most unknown stages of the Bonelli's eagle's life cycle so far, mainly because of the long-distance movements these birds perform during this period. At present, the only available data came from traditional ringing, wing-tags, and radiotracking methods (e.g., [START_REF] Cheylan | Dispersion des Aigles de Bonelli Hieraaetus fasciatus juveniles bagués en France[END_REF]Real and Mañosa 2001;Balbontín and Ferrer 2009;[START_REF] Hernández-Matías | Determinants of territorial recruitment in Bonelli's Eagle (Aquila fasciata) populations[END_REF]). However, although necessary when no other information is available, these methods usually provide few data (with some exceptions, e.g., Hernández-Matías et al. 2010), are highly time consuming and may not be effective at gathering good-quality information about eagles' movements, given the potential bias due to birds' movements outside surveyed areas and the limited accuracy of data that can be obtained. As an alternative, satellite telemetry allows continuous tracking of the individuals, regardless of their ranging patterns and the geographic extension of their movements [START_REF] Cadahía | Survival and movements of satellite-tracked Bonelli's Eagles Hieraaetus fasciatus during their first winter[END_REF][START_REF] Soutullo | Post-fledging behaviour in Golden eagles Aquila chrysaetos: onset of juvenile dispersal and progressive distancing from the nest[END_REF]. Although this technique is expensive in economic terms, hence limiting the number of birds that can be tracked, its main advantage is that it is especially useful to obtain accurate locations systematically and permits long-term tracking of birds' movements, in some cases as long as birds are recruited in the breeding population [START_REF] Urios | The first case of successful breeding of a Golden Eagle Aquila chrysaetos tracked from birth by satellite telemetry[END_REF][START_REF] Cadahía | Natal dispersal and recruitment of two Bonelli's eagles Aquila fasciata: a fouryear satellite tracking study[END_REF]). This information is therefore especially useful in identifying the main threat factors in risk-assessment studies aimed at establishing optimal management actions. This paper presents a large-scale outline of juvenile Bonelli's eagle dispersal areas in the Iberian Peninsula. Interestingly, there seems not to be a few, clearly delimited, overlapping, dispersal areas within the Iberian Peninsula.

By contrast, although birds tracked in this study come from a wide geographic range, there is no clear overlap between juvenile dispersal areas, and each bird seems to use a different one during their first years of life. In fact, 17 dispersal areas were detected for 11 birds, with some animals using more than one. This individual variation has important management implications and therefore suggests that conservation efforts should focus on the whole landscape matrix of man-managed ecosystems rather than in a few clearly delimited geographic areas.

Our results show that the first months of dispersal are made up by several phases that probably reflect successive stages of the species' ontogeny (Fig. 2; [START_REF] Soutullo | Post-fledging behaviour in Golden eagles Aquila chrysaetos: onset of juvenile dispersal and progressive distancing from the nest[END_REF]. Initial movements take place within the parental territory and represent the so-called dependence period, in which juveniles still depend upon their parents in terms of food supply [START_REF] Real | Post-nestling dependence period in the Bonelli's eagle Hieraaetus fasciatus[END_REF][START_REF] Ferrer | The Spanish imperial Eagle[END_REF]. Fledging occurs in Spain when nestlings are 44 to 69 days old [START_REF] Real | Post-nestling dependence period in the Bonelli's eagle Hieraaetus fasciatus[END_REF][START_REF] Mínguez | Factors influencing length of the post-fledging period and timing of dispersal in Bonelli's eagle (Hieraaetus fasciatus) in Southwestern Spain[END_REF], and the onset of dispersal we registered here took place between 114-177 days old (Table 2). Hence, the post-fledging dependence period in Bonelli's eagle lasts 70-108 days, which is in agreement with data previously reported when studying the species by other methods [START_REF] Real | Post-nestling dependence period in the Bonelli's eagle Hieraaetus fasciatus[END_REF][START_REF] Mínguez | Factors influencing length of the post-fledging period and timing of dispersal in Bonelli's eagle (Hieraaetus fasciatus) in Southwestern Spain[END_REF]Balbontín 2003). Average age at the onset of dispersal is coincident with former studies with the species, with reported data of 142 days old [START_REF] Cadahía | Survival and movements of satellite-tracked Bonelli's Eagles Hieraaetus fasciatus during their first winter[END_REF], 147 days old (Balbontín 2003), 149 days old [START_REF] Mínguez | Factors influencing length of the post-fledging period and timing of dispersal in Bonelli's eagle (Hieraaetus fasciatus) in Southwestern Spain[END_REF], and slightly lower than the 163 days reported by No. number [START_REF] Real | Post-nestling dependence period in the Bonelli's eagle Hieraaetus fasciatus[END_REF]. In other raptor species, like Spanish Imperial eagle or Golden eagle [START_REF] Ferrer | The Spanish imperial Eagle[END_REF][START_REF] Soutullo | Post-fledging behaviour in Golden eagles Aquila chrysaetos: onset of juvenile dispersal and progressive distancing from the nest[END_REF], a transitional phase between juveniles' independence from their parents and the definite departure from the parental territory has been described, named 'local dispersal' by [START_REF] Ferrer | The Spanish imperial Eagle[END_REF]. Unlike these species, Bonelli's eagle shows clear disperser behavior (sensu [START_REF] Walls | Movements of radio-tagged buzzards Buteo buteo in their first year[END_REF], and once juveniles leave the parental territory, they cover long distances, without remaining in the surroundings of their natal area. This becomes evident in the abrupt increase in the average distance to natal nest during the fifth and sixth month after birth in all birds (Fig. 2; for a further discussion on the estimation of the onset of dispersal in this species, see [START_REF] Cadahía | Estimating the onset of dispersal in endangered Bonelli's eagle Hieraaetus fasciatus tracked by satellite telemetry: a comparison among methods[END_REF].

Around the end of the first year, we observed a slightly (non-significant) decrease in the distance to natal nests (Fig. 2), which is caused by four juveniles' behavior. Interestingly, two males and two females performed short movements out of their usual dispersal areas and moved towards their parental territories. In these movements, approaches to the natal nests as short as 33 km were recorded. Similar results were found by Balbontín and Ferrer (2009) who also reported natal returns during the second year of 16 radio-tracked juvenile Bonelli's eagles coming from the Cádiz population (southern Spain). Returns to natal areas have been observed in other species, such as the Spanish Imperial eagle [START_REF] Ferrer | The Spanish imperial Eagle[END_REF], the Golden eagle [START_REF] Urios | The first case of successful breeding of a Golden Eagle Aquila chrysaetos tracked from birth by satellite telemetry[END_REF], or the Common Buzzard Buteo buteo [START_REF] Walls | Movements of radio-tagged buzzards Buteo buteo in their first year[END_REF], and were already suggested to occur in Bonelli's eagle (Real and Mañosa 2001). This behavior could be explained by food searching strategies based on their previous knowledge of the location Values represent mean±standard deviation. Note that for range-related calculations only n=7 females were used in the analysis a Only one or two locations were received after dispersing from the parental territory, so no range size could be computed for these birds b This bird did not start dispersal from the natal territory of prey patches and by checking the breeding population in the search for a vacancy in an active territory or a potential mate.

In relation to sex, significant interactions between sex and area of birth have been reported, with females dispersing farther than males and differing between populations [START_REF] Hernández-Matías | Determinants of territorial recruitment in Bonelli's Eagle (Aquila fasciata) populations[END_REF]. Different results were found by Balbontín and Ferrer (2009), who did not find between-sex differences in ranging behavior and movement patterns of juvenile Bonelli's eagles. The main difference between our study and others were the distances between the natal population and the dispersal areas, shorter in the case of Balbontín and Ferrer (2009), with two juvenile females recruited as far as 4.4 and 120.8 km from their natal nest, and larger in Hernández-Matías et al ( 2010) that reported a mean natal dispersal distance for recruited birds of 107.1±103.5 km, ranging from 19.4 to 430 km. In our study, only a female was recruited in the breeding population 441 km away from its natal nest [START_REF] Cadahía | Natal dispersal and recruitment of two Bonelli's eagles Aquila fasciata: a fouryear satellite tracking study[END_REF]). These results rule out the existence of compulsory philopatry in the species, and could be a consequence of the different origin of the birds tracked, from the Cádiz population (Balbontín and Ferrer 2009), Catalonia, and France (Hernández-Matías et al 2010) and from the eastern Iberian populations of the birds tracked in this study. Differences in ranging behavior and recruitment distances among birds of different geographic origin should be explored in detail in the future as more birds are tracked. It would be likely that dispersal areas in southern Spain could be acting as population sinks for juveniles coming from other Iberian populations (Moleón et al. 2009a). Geographic variation in prey availability could be an underlying mechanism explaining the tendency of birds of eastern populations to disperse further than those of southern populations (Moleón et al. 2009b).

The development of lightweight satellite tracking has enabled researchers to gain new insights into juvenile bird movements and areas covered during this important life stage of this endangered species. We have shown that juvenile Bonelli's eagles use during dispersal a number of areas distant from their parental territories. Our study corroborates the autonomous communities of Castilla-La Mancha and Andalucía (total surface=166.731 km 2 , 32.9% of the Spanish territory) to be those with the most important young Bonelli's assemblages (specially the provinces of Toledo, Albacete, and Cádiz), but also highlights the relevance of other areas in northern and eastern Spain (between Navarra and La Rioja, inner Catalonia, and southern Alicante; Fig. 1). Habitat characterization points out that juveniles concentrate in open habitats, particularly human-managed areas with extensive non-irrigated crops and herbaceous plants. Higher prey availability, such as rabbits or partridges in these open areas, along with the absence of breeding pairs, would account for this preference and for the spatial distribution of dispersal areas in the Iberian Peninsula [START_REF] Mañosa | Selection of settlement areas by juvenile Bonelli's eagle in Catalonia[END_REF]Real 2004;Moleón et al. 2009a). However, these areas pose important threats, like dangerous power lines, or direct persecution, since, in some instances, dispersal areas are placed within the limits of private hunting reserves in which poison to control predators is illegally used (Real et al. 2001;Real 2004).

The possible source-sink dynamics and the existence of several non-overlapping dispersal areas have major implications for the conservation of the species. Since dispersal areas are located over territories managed by different autonomous communities with particular jurisdictions, this brings into focus the need for organization among regional governments to undertake inter-regional conservation measures targeting the non-breeding fraction of Bonelli's eagle population. An adequate action plan for the species will need a combination of international and inter-regional coordinated actions aimed at improving juvenile survival. This, as demographic studies of population viability have demonstrated (Soutullo et al. 2008a), will ultimately be reflected in an enhancement of the population trend of this endangered species.

Fig. 1

 1 Fig. 1 Location of Bonelli's eagle juveniles' dispersal areas in Spain. Natal nests are represented by a star. Note that some birds used up to three distinct dispersal areas during natal dispersal

Fig. 2

 2 Fig. 2 Evolution of monthly distance to natal nest in 11 Bonelli's eagle juveniles during their first year of life. Black dots males; white dots females; dotted line all individuals' mean (standard error-SE lines are depicted in this case)

Table 1

 1 Summary data of 14 juvenile Bonelli's eagles studied by satellite telemetry in Spain

	Bird Type	Origin	No.	No.	Tagging	Signal	Transmitting	No.	Autonomous communities
		of PTT		locations	filtered locations	date	end	time (days)	dispersal areas	including dispersal areas
	1	Solar	Murcia	115	63	22/04/2002 01/12/2002	223	1	Murcia, Comunidad
										Valenciana
	2	Solar	Valencia	701	394	26/04/2002 12/06/2006	1,508	2	Comunidad Valenciana,
										Castilla-La Mancha,
										Murcia, Andalucía
	3	Solar	Alicante	300	148	08/05/2002 14/01/2005	982	1	Castilla-La Mancha
	4	Battery Alicante	144	64	08/05/2002 13/07/2003	431	1	Castilla-La Mancha
	5	Solar	Castellón	665	459	09/05/2002 04/03/2006	1,395	1	Castilla-La Mancha
	6	Battery Castellón	17	10	09/05/2002 31/12/2002	236	-	-
	7	Battery Barcelona	139	85	20/05/2002 23/11/2003	552	1	Castilla-La Mancha
	8	Solar	Alicante	25	15	30/04/2003 26/08/2003	118	-	-
	9	GPS	Castellón	885	876	14/05/2004 21/02/2005	283	2	La Rioja, Navarra, Cataluña
	10	GPS	Castellón	576	576	17/05/2004 13/11/2004	180	2	Andalucía
	11	Solar	Tarragona	248	160	11/06/2004 09/04/2006	667	3	Madrid, Castilla-La Mancha
	12	Solar	Tarragona	45	29	11/06/2004 20/09/2004	101	-	-
	13	Battery Alicante	125	85	11/08/2004 18/02/2005	191	2	Castilla-La Mancha, Andalucía
	14	Battery Alicante	120	67	11/08/2004 17/04/2005	249	1	Andalucía

Table 2

 2 Range-related variables and between-sex differences of 14 juvenile Bonelli's eagles tracked by satellite telemetry in Spain

	Bird	Sex	Dispersal date	Age at dispersal	Total range	Max. distance	Dispersal area	Distance dispersal
				(days)	size (km 2 )	nest (km)	size (km 2 )	area-natal nest (km)
	1	F	01/08/2002	150	5,292	90	903	81
	2	M	04/09/2002	177	15,205	367	2,132	245
	3	F	09/08/2002	150	980	185	264	148
	4	M	16/08/2002	158	39,130	589	6,929	421
	5	F	05/07/2002	114	6,692	541	844	442
	6	F	31/07/2002	135	_ a	367	_	_
	7	F	09/09/2002	163	24,938	663	6,409	534
	8	F	_ b	_	_	1 9	_	_
	9	M	20/08/2004	150	49,488	346	10,125	321
	10	F	22/08/2004	147	17,488	592	3,815	519
	11	M	02/10/2004	154	13,126	471	3,180	433
	12	F	15/09/2004	141	_ a	377	_	_
	13	F	21/08/2004	135	4,956	278	1,296	256
	14	F	03/09/2004	148	63,775	548	7,906	513
	Males (n=4)		2 September±21	160±12	29,237±17,930	443±111	5,592±3,657	355±89
	Females (n=7)		14 August±22	144±15	17,732±21,956	414±225	3,062±3,049	356±191
	Max.-min.		2 October-5 July	177-114	63,775-980	663-90	10,125-264	534-81
	Total		21 August±23	148±15	21,915±20,479	425±185	3,982±3,349	356±156

Eur J Wildl Res (2010) 56:923-930

Acknowledgments This project was principally funded by Terra Natura Foundation. The authors are indebted to the Conselleria de Territori i Habitatge of the Generalitat Valenciana (J. Jiménez, P. Mateache, A. Izquierdo, and A. García), Consejería de Industria y Medio Ambiente of Región de Murcia (E. Aledo and E. Cerezo), Departament de Medi Ambient of the Generalitat de Cataluña (X. Parellada), the University of Barcelona (N. Pocino, J. Real, and A. Tintó), the ICRA (M.R. Jané and T. Borau), the University Miguel Hernández (M. Carrete and J.A. Sánchez-Zapata), and the Spanish Ministerio de Medio Ambiente (V. García and P. García) for inestimable field assistance, permission to access the nests, and partial funding. M. Moléon, M. Ferrer, and anonymous referee made interesting comments in an early draft of this manuscript. L.C. and P.L.-L. were supported by FPU grants of the Spanish Ministerio de Educación y Ciencia (references AP2001-1444 and AP2005-0874, respectively). This paper was part of L.C.'s PhD thesis at the University of Alicante. The first two authors contributed equally to this paper.