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Lorenzo Quaglietta, Vania C. Eurasian otters Lutra lutra have been described in the literature as solitary, with the 2 sexes interacting only during mating. Data on otter sociality are rather scant, however, especially in Mediterranean regions, and the group formation documented in temperate zones has suggested some social plasticity. We investigated the sociospatial organization of a Mediterranean population of Eurasian otters by analyzing static and dynamic interactions among 15 individuals radiotracked during 3.

Contrary to what is described in the literature and expected for solitary animals, otter dy showed positive interactions, with individuals associating more often than expected by chance. Moreover, otter movement patterns were correlated. Finally, otters shared diurnal resting sites more often than expected.

Adult males and females with cubs overlapped spatially and temporally, even sharing resting sites when the males had no paternity. Nonrelated otter dy of opposite sex overlapped home ranges and core areas.

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Ranges of males overlapped with those of 1—3 females, whereas dy of the same sex exhibited almost no overlap, confirming the classic mustelid intrasexual territoriality and a polygynous mating system nevertheless, suspicions of female polyandry arose. On average, overlap of home ranges was higher than that of home-range cores.

Our contradict several statements in the literature on European otter sociality and reproductive behavior. We conclude that Eurasian otters are more social than ly thought, adding further evidence that social behavior in solitary carnivores may reveal ificant flexibility. The study of social interactions is of primary importance for understanding population dynamics, gene flow, genetic diversity Singleton and Hay ; Morin et al.

Although members of most species within the order Carnivora are regarded as solitary Gittlemanour comprehension of their sociobiology has, thus far, been limited Dammhahn and Kappeler In particular, dynamic interactions Doncaster have been poorly addressed in carnivores, because of intrinsic difficulties in obtaining simultaneous locations from 2 individuals Miller Moreover, although advances in global positioning system wildlife tracking now provide data in large volumes, proper analyses have not kept pace with the accumulating quantity of information Miller Classical methods for estimating dynamic interaction e.

These methods do not allow predictive inferences based on the development of spatially explicit null models to test actual movement patterns of wild animals, as is the case of mechanistic home-range e. Nonetheless, emergent, new modeling techniques provide promising alternatives. Among these, Long and Nelson proposed a new metric for estimating dynamic interactions based on the similarity or dissimilarity among independent movement patterns of tracked individuals.

And Miller created null models for independent individual movement using spatially explicit simulated data. Spatial patterns also are intimately associated with the mating system Clutton-Brock and Harveywhich is a distinct subset of interactions, being a crucial component of social systems Kappeler et al.

How opposite sexes of solitary carnivores interact prior to, during, and after mating, nevertheless, is another poorly described topic. Powell et al. Yet, for most Carnivora, research on reproductive behavior has concentrated on spatial overlap between the 2 sexes, neglecting the temporal dimension e. Thus, we know little regarding encounter rates between males and females, Text mates Evora phone sex if the movements of each sex, or of mating pairs, are related and eventually, when, how, and for how long.

ificantly, in the last 2 decades—since the 2 pioneering and most commonly cited studies of Powell and Sandell —the field of mating system and sociospatial organization of solitary carnivores has seen few ificant advances.

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Carnivore sociospatial organization is frequently assessed in relation to the availability of limiting resources or population density e. Environmental changes, kinship, and reproductive competition also may play a role Schneider and Kappeler Increasing evidence, nevertheless, suggests that mammals' social behavior is highly and individually variable, not easily categorized, and even reversible, being molded by ecological, evolutionary, genetic, developmental, and social factors Lott; Kappeler et al. For what concerns carnivores, some apparently solitary ones actually have complex social organizations Macdonald et al.

Solitary behavior may, in reality, equate to limited direct interactions among conspecifics while simultaneously allowing for a complex social system Gompper and Wayne Space use by mustelids, the family within the Carnivora with the most diverse members Wozencraftis best described by the classic model of intrasexual territoriality Powellalthough even this model may vary substantially among individuals within and among species Johnson et al.

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Both subfamilies of Mustelidae, the Lutrinae and Mustelinae, display some form of true sociality see reviews by Johnson et al. Eurasian otters Lutra lutra in north temperate zones display the classic mustelid model of intrasexual territoriality Erlinge ; Powell ; Green et al.

Eurasian otters have been described ly as solitary Erlinge ; Green et al. Nevertheless, describing members of a species as solitary implies few social interactions and an absence of cooperative behavior Sandell Despite extensive past research on Eurasian otters, these assumptions have not been tested.

The group range formation of otters described in the Shetland Islands Kruuk and Moorhouse ; Kruuk, and secondarily in streams located in China Hung et al. In particular, analyses of dynamic interactions among Eurasian otter dy are lacking, and no studies of otter sociospatial organization have been undertaken Text mates Evora phone sex Mediterranean areas.

We investigated the sociospatial organization of Eurasian otters in a Mediterranean environment by estimating the degree of spatiotemporal overlap among dy of radiotracked individuals in southern Portugal. In assessing static interactions Doncasterwe expected that spatial overlap would be restricted to individuals of the same sex as per the classic mustelid model of intrasexual territoriality Powell ; within dy of opposite sex, the proportion of home-range overlap would be higher for females than for males, as expected in a polygynous mating system Sandell ; and the extent of home-range overlap would be greater than overlap of home-range cores Kruuk and Moorhouse In our analyses of dynamic interactions Doncasterwe combined the use of the traditional, point-pattern, process-based method from Doncaster and 2 newer methods Shirabe [not seen, cited in Long and Nelson ]; Long and Nelson that assess potential correlations in movement patterns of simultaneously tracked individuals.

We hypothesized that otters would not be located together more often than expected by chance, and that movements of multiple individuals would not be correlated, in keeping with Eurasian otters being described as solitary and territorial Sandell Finally, we investigated spatial and temporal overlap of individuals at the microhabitat level by examining use patterns of diurnal resting sites by neighboring individuals and by comparing the frequency with which otter dy shared resting sites versus the probability of an individual using the site on its own.

We expected no resting site sharing both inter- and intrasexually, based on the literature Kruuk and Moorhouse Study area. The study area averaged m above sea level, was mostly flat, and included an extensive water network of streams, ponds, and small reservoirs.

Most people lived in cities and small villages. On the more detailed map, the small, internal minimum convex polygon refers to the area of the present study, where most of animals with neighboring or overlapping home ranges resided. Triangles indicate the spatial distribution of genotyped individuals coming from the extensive project. The dark-shaded area indicates the urban area, continuous lines indicate the water network, and the light-shaded area indicates the dams.

Animal capture and monitoring. Quaglietta and Quaglietta et al. We estimated age based on tooth wear, body dimensions, and development of sexual characters. In addition, cementum annuli analysis performed by the Norsk Institut for Naturforskning, Trondheim, Norway of canines extracted from radiotracked individuals that died, and otter carcasses from other studies, provided us with additional material for age comparisons.

We determined sex by direct observation of external anatomy and by genetic analyses. We estimated our average radiolocation error to be In addition, during the day, when otters were mostly inactive Quagliettawe determined the exact location of their resting sites via homing. We collected Text mates Evora phone sex locations fixes in h intervals and covered day and night with the same frequency. We took bearings no more than 15 min apart Schmutz and White We attempted to perform simultaneous continuous sessions for individuals with neighboring home ranges as often as possible.

Quaglietta et al. Home-range estimation. Otters, which use mainly linear habitats, present an additional challenge, because conventional home-range estimators are known to overestimate the area truly utilized by them Blundell et al. Most authors quantify otters' home ranges as linear stretches of rivers e.

We followed the approach of Melquist and Hornocker To assess home-range stability and the validity of our sampling, we tested for asymptotic range expansion Harris et al. Social interactions. In dy with home-range overlap, we also computed the overlap of cores. We computed static interactions in 4 different ways.

First, for each individual we calculated the percentage of home-range and core overlap in a dyad as the ratio between the portion of the waterway network shared by the 2 animals and home-range or core extension of that individual. The overlap within a dyad is, therefore, individual-specific Kernohan et al. Then, because overlapping area may be a poor estimator of the importance of some home-range areas Powellwe also calculated 3 indexes of utilization distribution overlap calculated using kernel estimator: the volume of the intersection VI— Seidel [not seen, cited in Kernohan et al.

For this, we compared the proportion of positive interactions in the observed simultaneous locations with the proportion of positive interactions in a set of simulated simultaneous locations obtained by permuting randomly all the locations coming from real simultaneous events of the dyad considered. Two fixes were considered simultaneous when we detected the 2 individuals within an interval of 1 h Gorman et al. Because Doncaster's method only looks at the spatial distribution of animal locations, we also investigated similarity among 2 individuals' movement trajectories.

For this, we used our continuous data to compute the correlation coefficient Cr of Shirabe [not seen, cited in Long and Nelson ] and the dynamic interaction DI index of Long and Nelson These 2 indexes measure the degree of correlation in movement data represented as a path as opposed to as points i. The DI index also provides a measure of Text mates Evora phone sex in 2 independent components of movement: direction often termed azimuth and speed.

To investigate males' spacing patterns as a function of the distribution and movements of the females present within their ranges, we analyzed the temporal variation of the DI index computed on single fixes of 4 male-female dy for which we had enough data M2 F1, M2 F3, M5 F8, and M5 F Furthermore, we calculated the percentage of consecutive time spent together i.

The latter was expressed as the of hours using 4 fixes as a proxy for 1 h that animal A was located together with animal B over the total of consecutive hours of their simultaneous monitoring. Finally, because we located otters sometimes Text mates Evora phone sex the same diurnal resting site, we performed a separate analysis considering only diurnal fixes, computing the frequency of the of times each dyad was found in the same resting site over the total of diurnal resting fixes in our data set of noncontinuous fixes.

This frequency was compared with the Ip index Powellwhich represents the expected probability of 2 animals being in the same site if they were using the space independently from each other. Statistical analyses. We used a chisquare test Minta to test for absence of positive dynamic interactions among simultaneously tracked pairs, comparing the proportion of positive simultaneous locations in the observed data set with the simulated expected by chance data set. We compared the observed frequency with which dy shared resting sites with the frequency predicted by the Ip index using a 2-tailed Wilcoxon ed-rank test.

Analyses were performed using R version 2. Home-range and relatedness estimates. We needed on average 49 fixes to get stable home ranges S1, DOI: S1roughly corresponding to 45 monitoring days. Of 16 otters with very-high-frequency transmitters, 14 7 males and 7 females provided data to estimate home ranges.

Twelve of these 14 otters had neighboring home ranges and all resided in the area represented by shaded polygon in Fig. M1 appeared to be another direct descendant of F1 Quaglietta et al. Female F8 was the daughter of M3. Summary of data for Eurasian otters Lutra lutra implanted with very-high-frequency transmitters. Static interactions. Therefore, we report mainly on the of the linear method. Two months after M2's death, a young adult male M4 was captured in the home range of M2, apparently having moved into the empty territory.

Subsequently, M4's home range overlapped extensively with those of adult females F3 and F13 Figs. Male M5, 1st captured as a juvenile, dispersed and thereafter overlapped with females F8 and F13 Fig. Linear home-range and core overlap in 8 male-female Eurasian otter Lutra lutra dy.

Linear home ranges of female and male Eurasian otters Lutra lutrd. The overlap between males is artificial, covering different time periods, except for M5 and M8, which overlapped concurrently only M5 is represented, for sake of clarity, because M8 is full sibling to M5. Moreover, their home ranges were separated by buffer areas Fig.

Dynamic interactions. Doncaster's method applied to single fixes showed positive interaction in almost all otter dy, with individuals associated within their related pairs more often than expected by chance Table 2. Additionally, although the data were too limited to be included in the analysis, juvenile male M3 was occasionally located together with unrelated female F1.

The ificant positive association between M5 and M8 mainly refers to the period when the 2 otters shared their natal home range. After Maywhen M8 started its dispersal see Quaglietta et al. Positive associations were not concentrated in any specific period of the year.

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