probability of the Biesbosch population to below 10% in .... one evening a week and determined the litter size by ..... (Fisher's Exact Test, n = 10, p < 0-05).
Biological Conservation 75 (1996) 125-137 Elsevier Science Limited Printed in Great Britain 0006-3207/96/$15.00+.00 ELSEVIER
0006-3207(95)00063-
1
DEVELOPMENT A N D VIABILITY OF A T R A N S L O C A T E D BEAVER Castor fiber POPULATION IN THE N E T H E R L A N D S B. A. Nolet* & J. M. Baveco DLO-lnstitute for Forestry and Nature Research, PO Box 23, NL-6700 AA Wageningen, Netherlands (Received 6 August 1994; revised version received 23 March 1995; accepted 31 March 1995)
necessary, neutralized (IUCN, 1987; Stanley Price, 1989). The loss of a species may indicate that the habitat quality at the site is no longer sufficient to support the species, or, alternatively, that the site cannot be recolonized naturally. In the former case, a translocation would be only a temporary 'face lift' for nature (Verkaar & Van Wirdum, 1991), and recolonization should therefore be identified as the limiting factor. The number of animals that can be translocated is constrained by the available funds, time and the size of the source population. As a result, the translocated population will initially be small and isolated. In small populations, stochastic processes play a major role in the dynamics, and persistence time tends to be short (Pimm et aL, 1988). The methodology to estimate the extinction probability of a small population, termed population viability analysis (PVA), has advanced considerably in the last decade (Shaffer, 1981; Boyce, 1992). Up to now PVAs have not helped to conserve endangered species in the wild, because the cause of the imminent extinction (e.g. overkill or habitat destruction) is not considered in these analyses (Caughley, 1994). However, they have contributed to the preservation of captive populations which are threatened by small population size and isolation. Recently, simulation modelling has become a popular approach to perform a PVA; see for example VORTEX (Lacy, 1993) and the RAMAS family of models (Ferson et al., 1988). In this approach the dynamics of a stage-, age- or size-structured population is calculated on a fixed timestep base. In general, the deterministic version of such matrix or difference equation models allows for the calculation of an asymptotic population growth rate and population structure (the largest eigenvalue and its eigenvector) (Caswell, 1989). However, these values are of little use in considering short-term prospects of a population. For viability assessments the models are extended to account for demographic and environmental stochasticity in mortality and reproduction rates, and for the occurrence of catastrophes. Furthermore, a regulatory mechanism (acting through density dependence) is usually incorporated to keep the modelled population from growing exponentially. Since the models are stochastic, for each set of parameter values a large number of simulations are performed; the results are presented as distributions of, for example, extinction probability.
Abstract
We monitored survival, reproduction and emigration of a translocated beaver Castor fiber population in the Netherlands for five years and used a stochastic model to assess its viability. Between 1988 and 1991, 42 beavers were released in the Biesbosch National Park. The mortality was initially high but gradually fell to normal rates. However, the breeding success was low, and we hypothesized that this was either a temporary phenomenon (the translocation hypothesis) or a permanent feature (the poor habitat hypothesis). According to the computer simulations, the isolated population was viable under the first but not under the second hypothesis. In the latter case, the prospects generally improved by the foundation of another population in the Gelderse Poort (100 km from the Biesbosch). However, this second habitat shouM be optimal for beavers in order to reduce the extinction probability of the Biesbosch population to below 10% in 100 years; the loss of genetic variability (1-2% per generation) was just above the applied tolerable risk (1%), but the effects of inbreeding are unknown in beavers. We conclude that the beaver population in the Biesbosch is not viable unless the reproductive success increases, either in the Biesbosch itself or in a nearby population. We recommend applying such viability analyses to evaluate the likely success of any translocation. Keywords." population viability analysis, reintroduction, translocation, simulation model, Castor fiber. INTRODUCTION The deliberate translocation of wild-caught animals (or plants), in an attempt to restore a locally extinct population within its former range, may become an increasingly important tool in nature conservation (Griffith et al., 1989; Harper, 1992). The goal is the re-establishment of a viable population and the technique may be applied both in order to save endangered species and to restore the functions of keystone species. However, there is an urgent need for more case studies. Before a translocation is undertaken, the cause of the preceding local extinction should be elucidated and, if *Present address: Netherlands Institute of Ecology, Centre for Limnology, Rijksstraatweg 6, NL-3631 AC Nieuwersluis, Netherlands. 125
B. A. Nolet, J. M. Baveco
126
0, 1020304050km •
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Fig. la. The current distribution of the beaver in the lowlands of northwestern Europe. Dots indicate recent reintroductions. Fig. lb. Positions of the Biesbosch and the Gelderse Poort along the rivers Rhine and Meuse in the Netherlands. Habitat restoration is planned in the shaded area along the river Waal, a tributary of the Rhine. As an example of the use and utility of viability analyses for translocated populations, we report here on the translocation of beavers Castor fiber to the Netherlands. Following severe overhunting only five small populations remained in Europe at the end of the 19th century (Freye, 1978). The last beaver in the Netherlands was killed in 1826 (Broekhuizen et al., 1992). Subsequently, beavers were translocated to several parts of Europe and at present number more than 500,000 animals (Schr6pfer et al., 1992). The debate to reintroduce beavers in the Netherlands started in the 1960s (Van Wijngaarden, 1966). Lebret (1976) suggested restoring the beavers' keystone function to riparian forests in the Netherlands (see Barnes & Dibble, 1988; Johnston & Naiman, 1990). The Biesbosch was the first area to release beavers, because it was considered large enough for a self-sustaining population of more than 50 animals (Van Wijngaarden, 1966; Werkgroep Bevers in Nederland, 1983). In 1988, a five-year experiment was started with the release of beavers in the Biesbosch. We monitored the reproduction, mortality, and emigration of the beavers in the Biesbosch, and subsequently projected the future population development using a simulation model. We assessed the viability of
the translocated beaver population under two hypotheses: the low observed proportion of pairs breeding was either (1) a temporary effect of the translocation (the translocation hypothesis); or (2) caused by the poor habitat quality of the release area, and was thus a permanent feature (the poor habitat hypothesis). We considered the following two risks tolerable: (1) a 10% probability that the population would go extinct within 100 years (Mace & Lande, 1991); and (2) a 1% loss of heterozygosity per generation (Soul6, 1980). In 1993, plans were made to reintroduce beavers at a second site in the Netherlands, the Gelderse Poort, 100 km from the Biesbosch along the river Waal (Helmer, 1993). We therefore also analysed the possible contribution of this future population to the viability of the beaver population in the Biesbosch.
METHODS Field s~dy Between 1988 and 1991, a total of 42 beavers from the Elbe (Germany, 51°45' N, 12o45' E) were translocated to the Biesbosch National Park (the Netherlands, 51o45' N, 4°50 ' E) (Fig. la) and released in October or November. The population was monitored up to the
Viability of translocated beaver population end of 1993. The Biesbosch is part of the freshwater estuary of the rivers Rhine and Meuse. The river water fluctuates with the tide with an amplitude of 20-30 cm, but high water levels are greatly affected by river discharge and the wind direction and force. The area (c. 100 km 2) is intersected by creeks, containing 615 km of bank, of which 185 km is wooded (Nolet, 1992). We classified the animals into age groups (juvenile, yearling, subadult or adult) on the basis of the body length:weight relationship. In the first two years of the experiment, the beavers were sexed by external palpation of the os penis (Osborn, 1955), but this technique was error-prone: three out of 23 animals (13%) checked by X-ray pictures or carcass analysis had been wrongly sexed. Four 'male' yearlings which subsequently paired with 'males' were clearly classified as females by a discriminant analysis (Norusis, 1988) using body length, tail length and tail width as the predictor variables (correctly classifying 68% of the 41 animals) and were thus regarded as females. Later, the presence of the penis bone was established by X-ray pictures. Before release, we marked the animals with coloured and aluminium earmarks for visual identification. Loss of aluminium earmarks was 50%, but only 9% of the coloured earmarks were lost. Radio-transmitters were implanted in 31 beavers (Nolet & Rosell, 1994). Transmitter life spans averaged 1.3 years + 0.3 SD (n = 21; of the remaining 10 radio-tagged animals, nine died before the transmitter expired and one dispersed out of the study area). The reception range was 300-600 m from a boat and 1-2 km from an airplane (details in Nolet & Rosell, 1994). In order to mark beavers born in the Biesbosch, we attempted to catch them at 1.5 years of age, when they were still with their parents. However, the tidal fluctuation of water levels in the Biesbosch negatively affected trapping success in Hancock live-traps and we only marked another four beavers (total trapping success 5%). In order to monitor survival and emigration, we regularly traversed the study area by boat and noted each sighting (an observation of a particular individual on a given day). In total, we obtained 2590 beaver sightings between 1988 and 1993. Radio-tagged beavers which had not been found by boat for two weeks were tracked by airplane. We visited all sites where a beaver was reported within the dispersal distance of beavers (170 km; Heidecke, 1984), and, if necessary, livetrapped the beaver in order to assess its origin. We classified an animal as deceased in a particular year when we did not observe it after 1 June of that year, the average date of birth along the Elbe (Heidecke, 1991). Because the data were too scarce to use more sophisticated methods, we simply assumed the mortality to be constant over the years. We calculated the mortality per age class as Na~/(Ndi + Nsi) × 100%, where Nai is the number of (supposedly) deceased animals per age class i, and Nsi is the number of animals surviving (for juveniles, yearlings and subadults, in which the duration of the age class is one year) or the number of years that animals of age class i survived (for adults).
127
Breeding was assessed by sound recordings of beaver pups inside the den using a voice-command cassette recorder. In July-August, we watched each den at least one evening a week and determined the litter size by counting the emerging pups. " The upper den chamber was located using fiberoptics (Karl Storz GmbH & Co, Tuttlingen, Germany). We measured the height of this chamber above the current water level with a 15 m long flexible hose filled with water. We recorded the current level of the river water at a nearby fixed measuring pole to relate chamber height to average sea level (Normaal Amsterdams Peil or NAP). The frequency of flooding of the beaver dens was estimated from measurements of the water levels between 1980 and 1992. The reference station in the Biesbosch was abolished at the end of 1985, but over the period 1980-1985 the daily high water levels measured at this station were strongly correlated (r2 -- 0-95, n -- 2192, p < 0.001) to those at the the main river and we used the linear regression equation to predict water levels in the Biesbosch after 1985. Simulation model An overview of the elements of our simulation model is given in Table 1. Population processes (reproduction, mortality and migration) were modelled sequentially within a timestep (one year) (Fig. 2). Our model was individual-based: each individual was followed separately (DeAngelis & Gross, 1992). This enabled us to keep track of the genetic composition of the population. The model was constructed and analysed in the Table 1. Parameters of the simulation model Stages: juvenile, yearling, subadult, adult Maximum reproductive age Stage-specific mortality rates (means of binomial distributions) Environmental variation (SD of the means of the binomial distributions) Density dependence (per stage) b'" Sex ratio at birth Litter size frequency distribution (1-5 offspring) Breeding fraction females (mean of a binomial distribution) Environmental variation (SD of the mean of the binomial distribution) Density dependence (Elbe parameters) a Probability of catastrophe (50% reduction in breeding fraction) Carrying capacity (density) Interdeme dispersal (fraction of two-year-olds arriving at 50 and 100 km)
0, 1, 2, >2 years old 15 years 0.33, 0.5, 0.07, 0.07 a 0-021, 0.022, 0-011, 0.011
+0.122N; 50%
;+0.148N;+0.148N
0.17, 0.50, 0.17, 0.08, 0.08 a 0.31 a (0-634 Elbe) 0.035
+ 0.393 N - 0-668 N 2 0.06 ~ 1-03 individuals/km wooded bank ~ 0-044, 0.013
aValues obtained from the field study in the Biesbosch. bN = density (individuals/km). CAdded to stage-specific mortality rates. dAdded to breeding fraction of females.
B. A. Nolet, J. M. Baveco
128
I calculate truncate-to-K mortality
I
along the Elbe in 1958-1975 (Piechocki, 1977). Variation in stage-specific mortality rates was assumed to be completely correlated among stages (but not sexes), i.e. the same random number was used to derive their yearly value. Variation in reproduction and mortality were, however, not assumed to be correlated. A flooding catastrophe during the gestation or lactation period usually causes a 50% loss of beaver pups along the Elbe (Heidecke, 1991). Such a catastrophe was defined to occur when 90% of the upper chambers flooded in May-August, and its effect was modelled by a 50% reduction of the pairs that bred. Its probability of occurrence was estimated from the field study. Beavers are excellent swimmers and, subsequent to den departure, flooding was not an important cause of death along the Elbe. Not a single flood victim was found in the summer in 25 years (Piechocki, 1977). Since our own observations in the Biesbosch are in agreement, we assumed that summer flooding did not affect mortality. We did not simulate catastrophic outbreaks of parasites or diseases, because in contrast to the American beaver, which is highly susceptible to tularemia, no epidemics have been reported to affect Eurasian beavers at the population level (Roma~sov, 1992).
I new number pOpulati°n s state
I
Density dependence
for all years: for all populations: set yearly rates
breedingfraction(incl.catastrophe) mortalityprobabilities for all or subset of individuals: calculate reproduction (adults) 1. belongs to breeding fraction? 2. create pair bonds, if absent 3. determine littersize (1 to 5) 4. determine sex offspring calculate mortality (all) 1. check for maximum age 2. is dying? (stage-specific prob.) calculate emigration (two-year
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age-andstage-structure Fig. 2. Schematic representation of the simulation model. object-oriented programming system Smalltalk, making use of the toolkit EcoTalk (Baveco & Smeulders, 1994). For a more extensive analysis of the impact of the current assumptions on PVA results, as well as alternatives relating to aspects of social behaviour, habitat selection, dispersal, and environmental stochasticity, we refer to Baveco and Nolet (in prep.). The main assumptions, and the origin of parameter values, are discussed in the next section. Assumptions in which our model differs from, for example, VORTEX include stable pair bonds, density dependence in both reproduction and mortality, and dispersal of subadults only.
Environmental stochasticity The environmental variation in annual reproduction and mortality was estimated from the observed variance in the Elbe population. The demographic variation was the variance expected for a binomial process (Lacy, 1993). The environmental variation was the variance in the binomial parameter (the proportion of 'successes', i.e. pairs breeding or animals dying) across years (see Appendix 1). The data used were: (1) the number of breeding pairs and the total number of pairs in a sample of the Elbe population in 1973-1991 (D. Heidecke, pers. comm.); and (2) the number of beavers found dead and the total number of beavers present
The density dependence of the death rate was modelled according to the stage-specific mortality rates of beavers in the source population along the Elbe between 1950 and 1990, in which time period the density increased more than six-fold (Heidecke, 1984, 1991). Juvenile mortality (r 2 = 0.98, n = 4 decades, p = 0.011) and the mortality of subadults and adults (r 2 = 0.56, n = 2 × 4 decades [pooled data], p = 0.033) increased linearly with density, whereas yearling mortality was density-independent (p = 0.33). The stagespecific death rates in the Biesbosch were assumed to run parallel to these lines with increasing density.
Carrying capacity The size of the beavers' territory was strongly dependent on the order of release. In their first year in the Biesbosch, the beavers released in 1988 held territories five times as large as the beavers released in 1991. In 1993, the former still claimed territories three times the size of the latter (Nolet & Resell, 1994). In contrast, winter territories were of constant size throughout the study. In the first two years of the study, territories were small in the winter and large in the summer; but such a seasonal pattern was no longer found in the later arrivals. Since these beavers daily patrolled their territory, containing on average 3-0 km of wooded banks, we expect all territories eventually to shrink down to this size (Nolet & Resell, 1994). The density at carrying capacity was calculated from the average number of inhabitants per territory (3.1 _> 1-year-old beavers; Heidecke, 1984) to be 1.03 individuals/km of wooded bank. In the model, the population was truncated to carrying capacity if the population size
Viability of translocated beaver population
100
exceeded the carrying capacity before the (densitydependent) birth and death rates were in equilibrium. This was achieved in a probabilistic way, by defining an additional chance of mortality for each individual, proportional to the relative size of the overshoot.
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In order to track the loss of genetic variability, all animals were assigned two unique alleles at the start of each run. The expected allozygosity (the percentage of animals having two alleles not identical by descent) was calculated assuming a Hardy-Weinberg equilibrium, according to the equation:
.
.
where Pi refers to the frequency of occurrence of allele i in the total allele population. The observed allozygosity was simply the percentage of animals in the population being allozygote (Hartl, 1980). In our analysis we focussed on the decrease in expected allozygosity as a measure of the loss of genetic variability. We assumed stable pair bonds, with surviving members of a beaver pair only mating again after the death of their mate, as in American beavers (Svendsen, 1989). In the model, an unmated adult female randomly selected a mate from the pool of unmated adult males.
Scenarios and metapopulation assumptions We hypothesized that the proportion of pairs that bred would develop in one of the following two ways: (1) the translocation hypothesis." translocated animals reproduced 50% less well than animals in the source population, but animals born in the Biesbosch reproduced as well as the beavers in the source population. Thus, the density dependence in birth rate was identical to that along the Elbe once translocated females were no longer a part of the breeding pool (Fig. 3), (2) the poor habitat hypothesis." the proportion of pairs that bred remained permanently low, being so low that no density dependence was postulated (Fig. 3). Under the latter hypothesis, we assessed the prospects of the beaver population in the Biesbosch in different scenarios: (1) a single population: no migration, and (2) after a supplementary release: 20 or 40 beavers were projected to be released in the Gelderse Poort (115 km of wooded banks; Helmer, 1993) in 1994 (Fig. lb). This supplement led to: (2.1) a two-deme metapopulation: no beavers settling between the Biesbosch and the Gelderse Poort. The distance between the demes was 100 km; (2.2) a three-deme metapopulation." settlement of beavers between the Biesbosch and the Gelderse Poort after restoration of 150 km of wooded banks along the river Waal (LNV, 1990) (Fig. l b). This was assumed to lead to the development of a third deme after colonization from the Biesbosch or the Gelderse Poort. The mutual distance between demes was then 50 km; and (2.3) a superpopulation." following extensive habitat restoration, the exchange between the demes was expected to be such that they effectively became a single population. The habitat quality of the demes other than the
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Density (beavers/km) Fig. 3. The percentage of beaver pairs that bred in the source population along the Elbe between 1950 and 1990 (Heidecke, 1984, 1991). The density dependence was described by a second-order polynomial. At very low densities, the proportion of pairs breeding is assumed to be lower due to the Allee effect (Allee, 1938). It, current percentage in the translocated population in the Biesbosch, which is hypothesized to increase up to the values of the source population (the translocation hypothesis) or to remain constant at a low level (the poor habitat hypothesis). Biesbosch was postulated to be poor or rich, respectively (i.e. these demes developed according to the poor habitat or translocation hypothesis). A catastrophic year with respect to reproduction applied to all demes, since flooding will equally affect the various locations along the same river. Reproduction and mortality were assumed to be uncorrelated between the Biesbosch deme and the other demes. In the superpopulation scenario, obviously, one set of yearly values applied to the whole population. All two-year-old beavers were assumed to be potential dispersers. The probability that a disperser reached another deme was estimated from the number of beavers found at a given distance along the Elbe (Heidecke, 1984) (Appendix 2): the fraction of dispersers arriving at suitable habitat at a distance of 50 km or 100 km in one direction amounted to 1/4 × 0-177 -0.044 and 1/4 × 0.053 = 0.013, respectively. In the case of a two- or three-deme simulation, this fraction of two-year-olds was removed from the source deme. Consequently, the performance of these demes may have been slightly underestimated in the simulations compared to that of the isolated population whose size was not adjusted to account for emigration. The essential differences between the different scenarios thus relate to habitat quality, the combined carrying capacity, the area over which environmental stochasticity is assumed to be effectively correlated, and the exchange rate of migrants. For each scenario, we ran 100 simulations over 100 years, starting in 1994. Beavers released as adults were assumed to be 7.5 years of age at the time of release, the average adult age along the Elbe (Heidecke, 1984). Since the field study ended before the mortality of 1993
130
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Year Fig. 4. The cumulative number of beavers released, born or lost (found dead, not resighted or dispersed), and the resulting current population size (including juveniles) in the Biesbosch. Error bars indicate the range of the minimum and maximum estimate (i.e. the beavers which were not resighted were assumed to be dead or alive, respectively). The minimum estimate is considered to be close to the real number (see text). was fully assessed, we subjected the age structure of 1993 to the annual mortality measured in the previous years prior to the start of the model simulations. In order to assign an age to the beavers supplemented to the Gelderse Poort, a stable age distribution was fitted given the initial birth and death rates. We did not correct for a possibly high initial mortality after this translocation. We performed a sensitivity analysis by changing the input parameter values one at a time by 20% of the nominal value in the direction which increased the extinction probability. RESULTS
Population development in 1988-1993 The beaver population in the Biesbosch initially increased solely due to the release of more animals (Fig. 4). In 1993, the cumulative number of beavers born finally exceeded the cumulative number of animals lost (i.e. deceased, disappeared or dispersed), and the population further increased despite the fact that no more animals had been released in the preceding year. At least 13 males and 14 females of > 1 year old were present in the Biesbosch at 1 September 1993. The population density was 0,15 beavers/km of wooded bank. Until 1993, the growth rate of the Biesbosch population was low compared to other reintroductions of beavers in Europe (Fig. 5). In the five years of study, beavers were only reported from four sites outside our study area. However, emigration from the Biesbosch was recorded with certainty only once, in December 1991, when a radio-tagged adult female was located 50 km from the Biesbosch. Her emigration route was reconstructed from cut trees. At the other three sites, the beavers were traced back to
Fig. 5. The observed population geometric growth rate A (i.e. the factor by which the population increases per year) in reintroduced beaver populations in Europe. C) indicates the study population. The curve is the regression through the • data after log-transformation of the time scale. The Inn population (+) did not grow because most beavers dispersed away from the release site. (Data from Reichholf, 1976; Heidecke, 1986; Geiersberger, 1986; Zurowski & Kasperczyk, 1988; Ermala et al,, 1989; Kollar & Seiter, 1990; KlennerFringes, 1991; Pagel & Reeker, 1992; Ellegren et al., 1993; P. Langer, R. Schulte and G. Schwab, pers. comm.)
escapes from captivity (Nolet, 1995). Ten other beavers were not resighted in the study area for more than one year. Because no signs of these animals were found outside the Biesbosch although beaver cuttings are conspicious, we think that these beavers died rather than emigrated. Mortality was particularly high in the first year after an animal was released: 14 out of 42 animals were found dead within this first year, and another one disappeared, yielding a first-year mortality of 33-36%. Ten of the beavers died before 1 June, so that the mortality was 24-26% to that date. We used a log-linear model in order to investigate the association of the first-year mortality with the factors sex, age (juvenile or older) and site of settlement (in rich habitat or not; Nolet & Rosell, 1994). The interactions between the first-year mortality and sex (p = 0.11) or age (p = 0.085) were not quite significant. However, there was a significant interaction between first-year mortality and site of settlement (p = 0.0026), the first-year mortality being greater in beavers which did not settle within three months (floaters) or which settled in poor habitat (54%) than in beavers settling in rich habitat (11%). Rich habitat was defined as a territory with more than 25% of the banks covered with trees and shrubs (Nolet & Rosell, 1994). Given the exceptionally high mortality in the first year following the release, we excluded that year in the calculation of the stage-specific annual mortality rates in the Biesbosch. The resulting death rates are compared to those along the Elbe in the 1950s (Table 2), since at that time the population density there was about equal to the current density in the Biesbosch (Heidecke, 1984). Including a pup mortality of 10% (Heidecke, 1991), the juvenile mortality in the Biesbosch
Viability of translocated beaver population Table 2. Stage-specific annual mortality (%) of beavers
Stage Juvenile Yearling Subadult Adult
Biesbosch a
Elbeb
36c (14d) 50 (12) 9 (11) 9 (54)
47 19 12 8
aExcluding animals which died or disappeared within the first 7 months after their release. bin 1950s (Heidecke, 1984). "Excluding pup mortality of c. 10% (Heidecke, 1991). dSample size: number of animals or beaver-years (for adults). (46%) did not differ from that in the Elbe region. The subadult and adult mortality were also nearly equal in both areas. The yearling mortality was, however, more than twice as high in the Biesbosch than along the Elbe, but yearling mortality might have been slightly overestimated since a number of the yearlings were unmarked. Once breeding, the litter size in the Biesbosch was not statistically different from that along the Elbe (Table 3; Kolmogorov-Smirnov Z -- 0.5, NS). However, the percentage of pairs breeding was on average only 31% + 4 SE in the Biesbosch during the study period. This is small compared to the 68% recorded along the Elbe in the 1950s (Heidecke, 1984). Of 10 pairs for which we have data for at least two consecutive breeding seasons, six did not breed in both years, none was unsuccessful after a successful year, one bred following an unsuccessful year, and three bred in both years. Thus, there are indications that pairs could be characterized as good or bad breeding pairs (Fisher's Exact Test, n = 10, p < 0-05). Of the 13 pairs present in 1993, fertility (breeding success × average litter size) was not correlated with total territory size (p = 0.72), the length of wooded banks in the territories (p = 0.66) or the richness of the territory (p = 0.66). Richness was defined as the proportion of wooded banks in the territory, and was thus a measure of the supply of trees regardless of diversity (Nolet & Rosell, 1994). The Biesbosch largely consists of former willow coppices, and trees other than willows are scarce. On the dykes along three water reservoirs, however, other tree species have been planted, and beavers selectively feed upon these (Nolet et al., 1994). Fertility tended to be greater in territories which encompassed part of
1 2 3 4 5
such a dyke, and hence contained a greater diversity of tree species, but this association was not quite significant (p = 0.086). The average height of the upper chambers of the beaver dens was only 105 cm _+ 6 SE above sea level (NAP). The 90%-percentile was 133 cm +NAP. Thus, an average upper chamber was predicted to be regularly flooded in the course of the year, and even during the reproductive season in summer (Fig. 6). However, the water level exceeded 133 cm + N A P only once in May-August in the 13-year period of recording. The frequency distribution of high water levels in M a y August was skewed to the right. We therefore logtransformed the water levels, and approximated this frequency distribution with the normal distribution. The probability that the water level would exceed 133 cm +NAP was 0.0005 per day, giving the probability of a catastrophe as 0-06 per year (summer season of 123 days). Summer flooding was, however, uncommon in 1988-1992, after the release of beavers. In these years, the water level exceeded 105 cm + N A P only once in May-August, and was never higher than 133 cm +NAP. Breeding pairs were also not associated with high beaver dens (Fisher's Exact Test, n : 12, p : 0-24). We can therefore exclude the possibility that summer flooding has up to now played a significant role in the poor breeding success of the Biesbosch. Population viability analysis The simulated fate of the population was very dependent on the hypothesized development in breeding success. 30
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Table 3. Litter size distribution of beavers a
Litter size
131
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23 59 15 3 0
"Juveniles emerging from the den. bUnpublished data 1973-1991 (D. Heidecke, pers. comm.).
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175
Height (cm +NAP) Fig. 6. Frequency distribution of the height above sea level (NAP) of the upper chamber in the beaver dens, and that of the daily high water levels in 1980-1992, measured during the whole year and between May and August.
B. A. Nolet, J. M. Baveco
132
Table 4. Prospects of an isolated beaver population in the Biesbosch after 100 years under the translocation hypothesis
Extinction probability (%) (x 5: SD) Nominal case Sensitivity analysis: effect of a 20% change in nominal value of parameterd Maximum reproductive age Mortality rate Environmental variation in mortality Density dependence of mortality Sex ratio at birth Litter size Breeding fraction females Environmental variation in reproduction Density dependence of reproduction Probability of catastrophe Effect of catastrophe on reproduction Carrying capacity
Extinction timea (years)
0 1 5:0.9 20 + 4.0*** 0 0 5 -+ 2.2* 2 + 1.4 2 + 1.4 0 0 0 0 1 _+0.9
42 37 --
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Population sizeb (x 5: SE)
Expected~ allozygosity (%) (x 5: SE)
178 5:1.7
85-8 + 0.4
165 + 1.7"** 121 + 3.8*** 176 + 1.5 176 + 1.4 134 + 2-5*** 157 + 1.7"** 154 + 1.8"** 177 + 1-4 157 + 1-5"** 175 + 1.5 175 + 1-5 156 + 1.0"**
81-0 + 0.7 **~' 72-1 + 1.7"** 85.1 + 0.4 85.2 + 0.4 77.7 + 0.8*** 81-8 + 0.7*** 79-9 + 1.2"** 85.0 + 0.4 83-6 + 0.7** 84.7 5: 0,6* 85.2 5:0.4 84-2 + 0.5**
*One-tailed p < 0.05; **p < 0.01; ***p < 0.001. aMedian of populations going extinct. bSurviving populations; differences tested with t-test with pooled or separate variance estimates where appropriate according to F-test. c1% loss of ailozygosity per generation (generation time = 7.3 years) is equivalent to a final expected allozygosity (alleles not identical by descent) of 86.3%. din the direction which increases the extinction probability.
Under the translocation hypothesis, the deterministic geometric growth rate A (calculated from the life table) was 1.075 once the adaptation problems were overcome. None of the simulated populations went extinct within 100 years. The final expected allozygosity was 85.8% + 0.4 SE, equivalent to a loss of allozygosity of 1.04% per generation (generation time -- 7.3 years). Thus, the extinction probability was much less than the tolerable risk, whereas the loss of genetic variation was about the tolerable risk. The extinction probability was sensitive to changes in mortality rates and, to a lesser extent, sex ratio at birth, but not to changes in the other parameters (Table 4). The final population size and expected allozygosity proved, however, more sensitive to parameter changes (Table 4). In contrast, h was less than one (0-976) under the poor habitat hypothesis. Consequently, 80% + 4.0 SD of the simulated populations went extinct. The loss of allozygosity was 3.9% per generation (generation time -- 7.9 years) due to the small sizes of the surviving populations (on average 26 + 6.0 SE). Thus, both losses exceeded the tolerable risks. The effect of a future release of beavers in the Gelderse Poort on the Biesbosch population was different in each scenario. If this second population also developed according to the poor habitat hypothesis, the extinction probability and the loss of allozygosity would be significantly reduced in the two-deme metapopulation and superpopulation scenarios, but the Biesbosch population would still not be viable (Fig. 7). In the superpopulation scenario, the median time to extinction would significantly increase from 54 years to 77 (p = 0.0030, median test) and 81 years (p = 0-0015)
after a supplement of 20 and 40 animals, respectively. The superpopulation performed better than the isolated population because of the larger number of founders and, probably to a lesser extent, an increase in carrying capacity (from 190 to 465 individuals). In the two-deme metapopulation the moderate exchange of dispersers, and the asynchrony in environmental stochasticity between the demes, was apparently just enough to improve the prospects of the Biesbosch population slightly. In the three-deme metapopulation scenario, the habitat along the river Waal was regularly colonized by dispersers from the other two demes. However, because the habitat was postulated to be poor, it did not grow and tended rapidly to become extinct again. Since we made the obvious assumption that there was no direct exchange of dispersers between the Biesbosch and the Gelderse Poort, dispersers were effectively trapped in the intermediate area. The third deme thus acted as a sink, hardly producing any dispersers that could have contributed to the persistence of the Biesbosch deme (Fig. 7). If, on the other hand, the second population developed according to the translocation hypothesis, the prospects of the beavers in the Biesbosch would be brighter, in particular when beavers could settle along the river Waal (Fig. 7). Once colonized, the third deme grew rapidly in this case, and contributed significantly to the prospects of the Biesbosch deme. In the threedeme metapopulation scenario with 40 animals supplemented, the extinction probability was 1% + 0.99 SD, and the loss of allozygosity would be 1.4% per generation. The simulation outcome was robust in all scenarios except in the two-deme metapopulation, where t h e
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Fig. 7. Extinction probability and final expected allozygosity (mean + SD) of the translocated beaver population in the Biesbosch under the poor habitat hypothesis. Beavers were supplemented in the Gelderse Poort leading to a two-deme metapopulation (2d-MP), a three-deme metapopulation (3dMP), or one superpopulation (SP). The second deme in the Gelderse Poort and the optional third deme, situated between the Biesbosch and the Gelderse Poort along the river Waal, developed according to either the poor habitat hypothesis or the translocation hypothesis (see text). C), significantly different from the isolated population scenario (no animals supplemented); ~, third deme acted as a sink; - , tolerable risk limits: an extinction probability of 10% in 100 years, and a loss of allozygosity of 1% per generation, respectively.
extinction probability was sensitive to a 20%-change in the migration rate (Fig. 8). This supports our finding that in the two-deme scenario the exchange rate over a 100 km distance is a crucial parameter. The final expected allozygosity was significantly reduced after a 20%-change in carrying capacity in the superpopulation scenario with 20 animals supplemented, but did not change in the other scenarios (Fig. 8). DISCUSSION All conditions were met to reintroduce beavers in the Netherlands. Natural recolonization from the nearest population along the Elbe (500 km as the crow flies) was unlikely to take place within the next century or so, because beavers would have to cross three water divides which act as natural barriers (Hartman, 1994) (Fig. l a). Overhunting, the probable cause o f the local extinction of beavers in the Netherlands, could nowadays be prevented by legislation. Despite the dense human population (393/km 2, De Vries & Wieringa, 1991), suitable habitat also still seemed to be present.
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Fig. 8. Sensitivity of the extinction probability and final expected allozygosity to a 20% decrease in migration rate (two-deme and three-deme metapopulation scenario) or to a 20% decrease in carrying capacity (superpopulation scenario). O, significantly different from the simulation outcome at the nominal value in the same scenario. See Fig. 7 for further details.
However, the success of a translocation exercise could only be tested in practice. Field observations During the beavers' first year in the Biesbosch, mortality was high compared to values reported in other translocations (17% by Heidecke, 1986; 14% by Zurowski & Kasperczyk, 1988). At least four beavers died from pseudotuberculosis, which is known to infect animals under stress conditions (Mair, 1968; Wetzler, 1981). In addition to human-induced stress, Nolet and Rosell (1994) showed that the subsequent releases were under severe competition for territories with animals released earlier. Because of this, the release of more beavers in the Biesbosch does not seem a good management option. Once settled, the mortality was about normal. On the other hand, the proportion of pairs that bred remained low in the Biesbosch during the 5 years of study, being about half as great as in the source population along the Elbe. There are indications that the Biesbosch is not such a rich habitat for beavers as previously thought. In earlier papers, we suggested that the low proportion of pairs breeding was caused by the scarcity of other food sources than willows, particularly waterplaints and herbs o f pioneer communities, which are needed to obtain specific nutrients such as phosphorus and sodium (Nolet et al., 1994, 1995). In this study, we
134
B. A. Nolet, J. M. Baveco
found a weak association between fertility and access to non-willow tree species.
Simulated population dynamics The general results from the single population and metapopulation-based PVA can be stated as follows: (1) Under the translocation hypothesis, the demographic characteristics of the Biesbosch population are such that a rapid growth to local carrying capacity is predicted. In that case, the mortality rate is the most sensitive demographic parameter, as found for other long-living species (Boyce, 1992). The measured environmental variation in mortality and reproduction rates of the Elbe population is low; this may be due to the beavers' unusual ability to modify their environment by building dens, dams and food caches. Increasing the environmental variation by 20% does not appear to affect population persistence in the Biesbosch setting. However, we have no guarantee that these values also apply to the Biesbosch. (2) Under the poor habitat hypothesis, increasing the area of suitable (albeit poor) habitat for a single well-mixed population improves the prospects of persistence. This result is bound to emerge from any PVA, since increasing population size reduces the impact of demographic stochasticity. (3) The foundation of a second population in the Gelderse Poort may enhance the prospects of the Biesbosch population considerably, even if both areas consist of poor habitat, provided there is a minimum rate of exchange. Again, this is in accordance with what we would expect from general metapopulation theory; of interest is a more quantitative insight in the required exchange rate. (4) Creation of a corridor by habitat restoration was the best option to enhance persistence of the Biesbosch population, provided the restored habitat was optimal. If the restored habitat was poor, this option appeared worst, since the corridor acted as a sink. This phenomenon illustrates that a thoughtless application of metapopulation theory to conservation practice may not be without risk; see also Hengeveld (1995a, b). The weakest elements in the application of this type of structured population models lay in the absence of a mechanistic explanation for population regulation or explicit relations and interactions with biotic and abiotic environmental variables (Caughley, 1994). Many PVA models achieve regulation simply by including logistic or comparable formulations, with net intrinsic growth rate and carrying capacity as parameters. In our case the same effect was reached by density-dependent reproduction and mortality, and truncation at carrying capacity. Since both elements will stabilize population size, we thus assumed that the underlying
mechanisms were different, with carrying capacity referring to an upper limit in the number of territories, and density dependence emerging from other causes. How well this represents the actual process in beaver populations is unknown. Especially the truncation-at-K rule is questionable, since when it occurs the additional mortality affects all individuals in the same way. A relationship with local habitat conditions is virtually absent in our model - - as in many others that are metapopulation-based. We based our scenarios on two parameter sets, relating population performance to habitat quality in a very crude way. The absence of an understanding of the mechanisms of population regulation and interaction with environmental variables makes it hard to value local habitat improvement or enlargement against management alternatives, such as the creation of corridors or a network of local populations. However, since we focussed on the fate of a specific population in a specific area, we do not expect its reliability to benefit much from a more mechanistic approach.
Population genetics In our analysis, a population with a 10% probability of going extinct within the next 100 years (the tolerable risk on demographic grounds) would lose about 1-2% allozygosity per generation, just above the tolerable risk based on genetic considerations. It should be noted that the actual loss of genetic variation might be greater than indicated by our analysis because some pairs are more successful than others, leading to a reduction of the effective population size. However, since the effects of inbreeding are poorly understood (Boyce, 1992; Lacy, 1992), management proposals to reduce further the loss of genetic variability below 1% per generation are not justifiable. First, the 1% tolerable risk is a more conservative value than the 2-3% applied as a rule of thumb by animal breeders (Soul6, 1980). More importantly, the effects of inbreeding may vary widely among mammal species (Ralls et al., 1988; Caughley, 1994). In Eurasian beavers, inbreeding might not cause serious problems. A translocation of only 80 beavers to Sweden between 1922 and 1939 led to a healthy population of 100,000 animals in 1993, although the genetic variability among these animals was small (Ellegren et al., 1993). An inbred captive population originating from only 15 beavers formed a successful source for the reintroduction of beavers in Poland (Zurowski, 1989). The only study which indicates that inbreeding might negatively affect beavers is by Savelyev (1989), who found that the incidence of dental anomalies was far greater (>30%) in introduced, inbred American beavers in eastern Russia than in the endemic populations of Eurasian beavers (
