The study area comprised lowland peat marshes in the north of the Netherlands, ca. 200 km2 in extent and located at 52°38′–52°50′ N, 5°53′–6°09′ E. The area consists of a mosaic of peat grasslands, reed beds (Phragmites australis) and swamp woodland, mainly composed of Willow (Salix spp.), Black alder (Alnus glutinosa) and Birch species (Betula spp.) intersected by small ditches and pools. Most of the surrounding landscape is intensively farmed. The mean annual temperature is 9.5°C and on average there are 10 frost days per year. The area can be divided into three zones: the Weerribben and the Rottige Meenthe, which comprise peat grassland, woodland and ditches, and the Wieden, where larger lakes are also present (Fig. 1).
Origin and release
The otters used in the Dutch reintroduction project had either been captured in the wild in Belarus, Latvia, or Poland, or originated from captivity or rehabilitation programmes in Sweden (Finnish origin), the Czech Republic, or Germany. The otters caught in the wild came from areas with high otter densities. Between July 2002 and April 2008, 30 otters were sequentially released in the study area (Table 1). The first set of otters was released in the Weerribben, the central location, and in subsequent years otters were gradually added to the Wieden and Rottige Meenthe areas (Table 1). At the time of release the animals varied in age between 1 and 5 years old. Before their release, tissue and blood samples were taken for DNA fingerprinting and all the otters were tagged with a transponder and were fitted with a radio transmitter, implanted intraperitoneally, for monitoring initial post-release movements and survival. The implantations were carried out by a veterinarian at Burgers Zoo (Arnhem, The Netherlands), where the otters were kept in captivity for 3–18 days and observed before being released. The study was conducted in accordance with Dutch legislation on the protection and welfare of vertebrate animals used for experimental and other scientific purposes.
Sprainting behaviour often shows seasonality and there is evidence that winter is the best period to collect otter spraints (Kruuk 1992) and that the microsatellite DNA analysis of otter faeces is most successful in cold months, when spraints are collected in the early morning (Hájková et al. 2006). During summer it is difficult to collect fresh spraints in our area because the tall grass and reeds obstruct visibility. Therefore, our surveys were carried out in the winter half year (October to the end of March) of consecutive years from 2002 to 2008.
Each winter period we checked the whole release area for otter activity (spraints, spoor, landing sites, trails). In November and December each year we did a first survey of the whole release area covering about 10–15 km2 per day by foot, bike and boat. From January to March we conducted a second survey. We tried to cover the whole release area at least twice and revisited promising sites suggested by the field managers. On average we spent 48 days in the field each winter, searching for otter marks. We tried to revisit each location from which we had collected a spraint, with the aim of obtaining at least 3 fresh spraints from that location. The constraints were the accessibility of the terrain and the availability of waterways. We used GPS to record the locations of spraints and thus ascertain the spatial organisation of the population. If possible, the area was visited the day before collection and old spraints were marked to increase the chance of identifying fresh spraints the next day. When this strategy could not be employed, we collected all the spraints that seemed to be fresh. To minimise DNA degradation, spraints were collected in the morning. The samples were immediately put into 10 ml plastic phials containing 99% ethanol and taken to the lab, where they were stored at −20°C until DNA extraction and analysis. A total of 1,265 spraints were collected for genetic analysis.
We conducted a vigorous publicity campaign to encourage people to contact us when dead otters were found, so that we would have a as complete picture of the population as possible. Dead otters were delivered to Alterra throughout the year and subjected to post mortem analysis to determine the most likely cause of death. Tissue samples from the cadavers were stored in phials containing 99% ethanol. Most of the otters brought in were road kills from outside the release area.
Rationale of the monitoring design
Since our otter population is small (n = 30 founders) and isolated, and immigration from Germany seems highly unlikely, it is effectively a closed population. At the start of the project we constructed a reference database of the genetic profiles of the founders, so that in subsequent years we could infer successful mating and recruitment from new genetic profiles obtained from spraints or dead animals. We updated the database of genetic profiles yearly. Since all potential parents were known, we applied complete exclusion as our method of parentage analysis (Blouin 2003; Jones and Ardren 2003). A spraint was classified as from an offspring if (a) the genetic profile did not match existing profiles from previous years, and (b) the profile could unequivocally be assigned to a known male and female. The offspring–mother–father combination was subsequently checked by comparing the distribution of GPS-coordinate observations of the animals involved.
Faecal DNA was extracted using a modification of the hexadecyltrimethylammonium bromide (CTAB)-based extraction (Parsons et al. 1999; Hung et al. 2004). This entailed removing a spraint from the phial of ethanol and briefly putting it on filter paper to remove most of the ethanol. Next, a raisin-sized piece was put in a 2 ml Eppendorf tube together with 1 ml of CTAB buffer (100 mM Tris–HCl pH 8, 20 mM EDTA, 1.4 M NaCl, 2% CTAB) and the spraint was homogenised by stirring with a small rod. After adding additional CTAB buffer to bring the total volume to 2 ml, the mixture was briefly vortexed and left on a shaker for 15 min. This mixture was centrifuged for 5 min and 1.5 ml of the supernatant was transferred into a new tube together with 0.5 ml chloroform. After two rounds of extraction, DNA was precipitated by adding 0.67 ml isopropanol to 1 ml of the cleared suspension. The resulting pellet was resuspended in 0.18 ml of ATL buffer. Spraint pellets and tissue from released and dead individuals were further processed following the protocol of the DNeasy Blood and Tissue Kit (Qiagen) for DNA purification.
During the first three winters seven microsatellites were sufficient for individual typing and parentage assessments: Lut701, Lut715, Lut717, Lut733, Lut818, Lut832 and Lut833 (Dallas and Piertney 1998). Subsequently because of the loss of released individuals, the occurrence of offspring and the increasing relatedness among individuals, we had to gradually increase the number of microsatellite loci: OT04, OT05, OT07, OT14, OT17, OT19 and OT22 (Huang et al. 2005) and RI18 (Beheler et al. 2005). We only used tetranucleotide microsatellite loci to reduce the occurrence of stutter bands and ambiguity in scoring that often happens with dinucleotide loci.
PCR reactions were performed in a total volume of 10 μl containing 0.3 Units of Taq (Invitrogen Taq DNA polymerase (18038-034), amounts of PCR buffer and W-1 according to the Invitrogen protocol, 130 nM of each primer, 200 μM of each dNTP, 4.25 mM MgCl2 and 320 μg/ml BSA. Forward primers were labelled with either an IRD-700 or an IRD-800. The PCR programme used was 95°C/3 min and (90°C/30 s, T
a/30 s, 72°C/1 min.) × 39 cycles. For most primers T
a was 60°C, except for locus Lut715 (T
a = 58°C), loci Lut733, Lut782 and Lut818 (T
a = 59°C), locus Lut717 (T
a = 61°C), and locus OT07 (T
a = 62°C). The same protocol was used for tissue extracts, except that a dilution factor of 10 was applied and 2 μl of this diluted extract was used. For sex identification we used the DBY7Ggu primer following the protocol of Hedmark et al. (2004).
PCR products of microsatellite loci and sexual typing were genotyped on a 6.5% polyacrylamide gel containing 7 M Urea and 1× TBE on a Li-Cor 4300 platform.
We did not use the same set of microsatellite loci every year because initially the seven loci of Dallas and Piertney (1998) had sufficient power to distinguish individuals and assess parentage. In 2006/07 these seven loci were still sufficient for identifying individuals, but not for assessing parentage. After optimising and adding the second set of loci we made two new sets of loci: (i) a set for distinguishing individuals (Lut715, Lut717, Lut733, Lut833, OT07, OT19 and OT22); and (ii) a set with the remainder of the loci, which we used solely to confirm parentage assessment or in cases of doubtful identification of an individual because of the failure of a locus. Budget constraints prevented us from using all loci. The criterion for compiling our first set of loci was a P
(ID)sib of < 0.01. The probability of identity, P
(ID), is the probability that two individuals drawn at random from a population have the same genotype at multiple loci (Creel et al. 2003; Taberlet and Luikart 1999; Waits et al. 2001). It is considered to be the most common statistic used to quantify the power of molecular markers in distinguishing two individuals. The P
(ID)sib, the P
(ID) among a population composed solely of siblings, gives an upper limit to the possible range of P
(ID) in a population. At the beginning of the project, in 2002/03, the P
(ID) among the released animals was 1.9 × 10−7 and the P
(ID)sib was 1.9 × 10−3. Because of the changing population composition, e.g. loss of released individuals, presence of offspring and increased relatedness, in 2006/07 P
(ID) was 4.1 × 10−6 and P
(ID)sib was 4.4 × 10−3. During the 2007/08 season the P
(ID)sib of our first set of loci was 2.1 × 10−3, but when all 15 loci were used it increased to 1.4 × 10−5.
To reduce the chance of mistyping, we applied a modified multiple tube approach (Gagneux et al. 1997; Hung et al. 2004; Taberlet et al. 1996). The constraint on the modified approach was that with our current protocol we could only run ca. 50 PCRs from one faecal extract and therefore had to adjust the number of replicates when using all 15 microsatellite loci. Our approach was as follows: (1) Each sample was amplified three times for locus LUT715. This locus was chosen because of good, repeatable results in previous experiments. (2) The sample was discarded from the subsequent analyses if there were less than three PCR products. In case of three PCR products a sample was still discarded if, after scoring the results, it resulted in three different typings. (3) Selected samples were amplified three times for the remaining loci from the first set. (4) Three independent typings with the same single allele at a locus confirmed a homozygote. Three independent typings with the same two alleles at a locus confirmed a heterozygote. Samples with two typings of a heterozygotes and one homozygous typing, were scored as heterozygous with the two alleles appearing in these typings. (5) For loci that were typed twice as homozygous and once as heterozygous, or for loci that were scored as homozygous for different alleles, three additional independent typings were performed. When among the six typings an allele was recorded at least twice, the sample was accepted as heterozygote. If an allele appeared only once among the six typings the sample was accepted as a possible homozygote. (6) Those samples that could not be appropriately typed up after six typing attempts were discarded. (7) When the genotypes of two samples were the same at six loci and the only mismatch at the seventh locus may have been due to allelic dropout, we considered the two samples to be the same multilocus genotype if they came from geographical locations close to each other. As safeguard, these samples were also typed for the second set of loci. If the only mismatch was an unambiguous different typing at the seventh locus, the samples were always typed for the second set of loci. (8) The consensus genotypes obtained were compared with the reference database and, if possible, assigned to known individuals. (9) In case of new profiles we tried to assess parentage and completed the profile for the remaining loci. Final parentage was assessed on 15 loci, with complete exclusion as the criterion (Blouin 2003).
Since we had complete genetic profiles for the otters released, we calculated allelic dropouts and false alleles as deviations from the expected profile after assigning spraint samples to known individuals. The allelic dropout for a locus was computed from the number of homozygotes typed for the heterozygous individuals, divided by the total number of heterozygous samples. Allelic dropout occurred in 15.2% of the heterozygous samples and varied among loci (range: 8.1% (LUT833)–22.4% (LUT717)). When using three independent amplifications, the probability of obtaining false homozygotes was 0.0018, using the equation P = K × (K/2)n − 1 (Gagneux et al. 1997), where K is the observed frequency of false homozygotes averaged over all individuals and loci and n is the number of repeated amplifications. Strictly speaking, false alleles are undefined amplification products that show up as a spurious or third allele. These occurred in only 2.1% of the PCR reactions. More broadly speaking, a heterozygous typing of a homozygote individual could also be considered as a false allele. The observed frequency of false heterozygotes was 14.9% and varied among loci (range: 4.0% (LUT733)–26.2% (LUT717)). As expected, these values are comparable to the allelic dropout results.