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Influence of weather factors on population dynamics of two lagomorph species based on hunting bag records

Authors:
  • Université Sorbonne Paris Nord
  • Jasja Dekker Dierecologie

Abstract and Figures

Weather conditions can have a significant influence on short-term fluctuations of animal populations. In our study, which is based on time series of hunting bag records of up to 28 years from 26 counties of The Netherlands and Germany, we investigated the impact of different weather variables on annual counts of European rabbits (Oryctolagus cuniculus) and European hares (Lepus europaeus). Overall, the long-term dynamics of both species could be described by higher-order polynomials. On a smaller time scale, the number of European hares shot was lower in years with higher amounts of precipitation during late summer/autumn, and the number of European rabbits shot was lower in years with high precipitation in spring of the respective year. We suggest that rainy weather conditions might have lowered the survival of young rabbits in spring and might have generally facilitated the outbreak or spread of diseases in rabbits as well as in hares, specifically in autumn. In addition, the results showed a time-delayed, interactive effect between precipitation in spring and winter weather on European rabbit dynamics: rabbit numbers were limited by low temperatures of the prior winter season, but only when precipitation was high during spring of the previous year. The latter result might be explained by thelowering effects of rainy spring weather on the body condition of the animals, leading to higher sensitivity to harsh winter conditions. In conclusion, our study provides evidence for the impact of weather conditions on the population dynamics of both study species and particularly highlights complex interactions between the prevailing weather conditions during different seasons in the European rabbit.
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ORIGINAL PAPER
Influence of weather factors on population dynamics
of two lagomorph species based on hunting bag records
Heiko G. Rödel &Jasja J. A. Dekker
Received: 28 October 2011 / Revised: 1 April 2012 / Accepted: 8 April 2012 /Published online: 28 April 2012
#Springer-Verlag 2012
Abstract Weather conditions can have a significant influ-
ence on short-term fluctuations of animal populations. In
our study, which is based on time series of hunting bag
records of up to 28 years from 26 counties of The Nether-
lands and Germany, we investigated the impact of different
weather variables on annual counts of European rabbits
(Oryctolagus cuniculus) and European hares (Lepus euro-
paeus). Overall, the long-term dynamics of both species
could be described by higher-order polynomials. On a
smaller time scale, the number of European hares shot was
lower in years with higher amounts of precipitation during
late summer/autumn, and the number of European rabbits
shot was lower in years with high precipitation in spring of
the respective year. We suggest that rainy weather condi-
tions might have lowered the survival of young rabbits in
spring and might have generally facilitated the outbreak or
spread of diseases in rabbits as well as in hares, specifically
in autumn. In addition, the results showed a time-delayed,
interactive effect between precipitation in spring and winter
weather on European rabbit dynamics: rabbit numbers were
limited by low temperatures of the prior winter season, but
only when precipitation was high during spring of the pre-
vious year. The latter result might be explained by the
lowering effects of rainy spring weather on the body condition
of the animals, leading to higher sensitivity to harsh winter
conditions. In conclusion, our study provides evidence for the
impact of weather conditions on the population dynamics of
both study species and particularly highlights complex inter-
actions between the prevailing weather conditions during
different seasons in the European rabbit.
Keywords European hare .European rabbit .Lepus
europaeus .Oryctolagus cuniculus .Precipitation .
Temperature
Introduction
The question of which factors are involved in shaping the
dynamics of animal populations is certainly one of the major
issues in population ecology. Next to density-dependent
processes, there is a large body of evidence that variation
in climate and weather can significantly affect vital rates and
thus can be decisive for changes in density in many pop-
ulations (e.g. Stenseth 1999; Aars and Ims 2002; Saether et
al. 2007). For example, weather effects, i.e. stochastic var-
iation in parameters such as temperature and rainfall among
or within years, have been reported to influence body con-
dition, survival and reproduction in many mammalian spe-
cies (small- and medium-sized mammals: Van Vuren and
Armitage 1991; Fichet-Calvet et al. 1999; large mammals:
Loison et al. 1999; Delgiudice et al. 1990). Such weather
effects are often complex and have the potential to interact
on multiple levels. For example, the effect of one weather
factor on an organism can intensify the effect of another
for example, in the combinations of low temperature with
rain and wetness or low temperature and wind (Seltmann et
al. 2009; Mercer 1998). Furthermore, the effects of weather
Communicated by C. Gortázar
H. G. Rödel (*)
Laboratoire dEthologie Expérimentale et Comparée E.A. 4443
(LEEC), Université Paris 13,
Sorbonne Paris Cité,
93430 Villetaneuse, France
e-mail: heiko.rodel@leec.univ-paris13.fr
J. J. A. Dekker (*)
Jasja Dekker Dierecologie,
Enkhuizenstraat 26,
6843 WZ, Arnhem, The Netherlands
e-mail: info@jasjadekker.nl
Eur J Wildl Res (2012) 58:923932
DOI 10.1007/s10344-012-0635-1
conditions that an animal experiences during different sea-
sons or developmental stages might interact. For example, a
study on European rabbits (Oryctolagus cuniculus) in Ger-
many showed that individuals that experienced high
amounts of rain during their early post-weaning life showed
comparatively lower growth rates until the end of their first
vegetation period. Later on, such animals suffering from
stunted growth had a lower chance to survive during the
winter season, in particular, when winter temperatures were
low (Rödel et al. 2004a).
Various mechanisms can underlie apparent correlations
between weather and changes in population size. On the one
hand, weather effects have the potential to directly influence
health, survival and body condition of the animals, e.g. by
increasing the costs of thermoregulation or by thermal stress
(Seltmann et al. 2009;Rödeletal.2009a; Myers et al.
1981). On the other hand, weather effects might act indi-
rectly. For example, low temperatures and snow cover can
limit the quality of or access to food (Rödel 2005; Crawley
1983). Moreover, adverse or extreme weather conditions,
such as persistent rain and wetness, can favour the spread of
diseases (O'Connor et al. 2006; Stromberg 1997), thus af-
fecting health and survival. Furthermore, unfavourable
weather conditions can increase the animalschance of
being predated by lowering their body condition or by
directly hampering their mobilityfor example, by high
snow depth (Cederlund 1982; Mech et al. 1987). Know-
ledge of such potential mechanisms, i.e. of how different
weather conditions can affect the health and survival of a
species, might help to conduct specific and targeted studies
in order to assess the effects of different weather variables
on population dynamics by considering potentially sensitive
periods of an animals life history.
In the present study, we focus on two lagomorphs, the
European rabbit and the European hare (Lepus europaeus).
Both species underwent a decline in Europe during the last
decades (Smith and Boyer 2006; Smith and Johnston 2008).
In the European rabbit, this decline started in Europe in the
1950s and was certainly in large part due to the outbreak and
spread of two viral diseases, myxomatosis and rabbit hae-
morrhagic disease (RHD), the latter spreading in Europe
(including Germany) in the late 1980s (Moreno et al.
2007; Delibes-Mateos et al. 2009) and arriving in The
Netherlands in the early 1990s (Drees et al. 2009; van Strien
et al. 2011). A strong decline from the 1960s and 1970s of
the last century onwards was also observed in European
hares (Mary and Trouvilliez 1995; Smith and Johnston
2008)the factors causing this population trend appear to
be more complex than in the European rabbit (Smith et al.
2005). It has been widely accepted that habitat changes
caused by the intensification of agriculture are a key factor
in driving the long-term decline in this species (Edwards et
al. 2000; Smith et al. 2005; Santilli and Galardi 2006;
Zellweger-Fischer et al. 2011). However, other factors such
as diseases (Lamarque et al. 1996), predators (Reynolds and
Tap per 1995; Schmidt et al. 2004; Knauer et al. 2010), land-
scape fragmentation (Roedenbeck and Voser 2008) and cli-
matic conditions (Kilias and Ackermann 2001;Jenningsetal.
2006; Spittler 1997) are also reported to play a role in shaping
European hare population trends.
In both species, several mechanisms of how weather and
climate can affect vital rates and population dynamics are
known from experimental as well as observational studies in
the wild or in the lab. In particular in European rabbits, such
studies have proven strong effects of weather conditions on
individual growth, health, survival and reproduction during
different life stages (reviewed Tablado et al. (2009); Rödel
and von Holst 2008). During early juvenile life, young
rabbits and hares are particularly sensitive to low temper-
atures and wetness, leading to increased metabolic costs
with potential implications for their health and survival
(Hackländer et al. 2002; Rödel et al. 2009a; Seltmann et
al. 2009). In addition, wetness in spring and early summer
has been shown to limit growth and body condition in
young rabbits (Rödel et al. 2004a). Later in the season,
low winter temperatures are reported to limit population
densities (Bijlsma 2004), in particular by lowering the sur-
vival probability of first-season animals (Rödel et al. 2004a;
Rödel and von Holst 2008). In accordance, a study on sur-
vival rates of yearling European hares conducted at the north-
ern edge of this speciesdistribution revealed lower survival
rates during harsh winters (Marboutin and Hansen 1998).
In a comparative approach based on long-term data sets
of European rabbits and European hares in The Netherlands
and in Germany, we explored the effects of weather con-
ditions (ambient temperature, precipitation) during different
times of the year on population dynamics. As direct and
long-term population counts in these species are rare and
only available on a local scale, we use time series of hunting
bag data as proxy for changes in population size. Based on
our assumptions on potential mechanisms as stated earlier,
we focus on weather conditions during spring, i.e. around
the onset of the breeding season, during summer/autumn
when population densities are usually high and diseases are
known to spread in populations of both species (Lenghaus et
al. 2001; Brooks 1986) and during winter when the avail-
ability of high-quality food is low (Reichlin et al. 2006;
Rödel 2005; Rödel et al. 2004b). Correcting for long-term
population trends, we (1) considered short-term effects of
different weather variables on the population dynamics in
both species in our models. We also tested potentially rele-
vant interactions among weather variables (2) within and (3)
across different seasons. In particular, we predict (a) that
high amounts of precipitation could enhance the detrimental
effects of low temperatures, e.g. during winter or spring, (b)
that adverse weather conditions during the vegetation period
924 Eur J Wildl Res (2012) 58:923932
might have the potential to increase the susceptibility of
animals to harsh conditions during the subsequent winter,
or vice versa, and (c) that low temperatures during the
winter might increase the susceptibility of the animals to
harsh conditions (low temperatures, high levels of precipi-
tation) during the early vegetation period.
Materials and methods
Study period and sample sizes
For this study, hunting bags (both species) from The Nether-
lands were available over a period from 1980 to 2007 for 11
counties. Data from Germany were available from 1982 to
2007 for the counties of former West Germany (n010) and
from 1987 to 2007 for the counties of the former German
Democratic Republic (n05). We did not consider the county
of Berlin (Germany), where hunting of European hares is
prohibited by law. Given some missing values for some
years in particular counties, this resulted in a total number
of N0661 annual hunting bag records of European rabbits
and European hares from 26 different counties.
Hunting bags were calculated as the summed up animal
numbers per annual hunting season (see Fig. 1). Data from
The Netherlands were provided by the Koninklijke Neder-
landse Jagersvereniging (Royal Dutch Hunter Association,
KNJV), which validated and stored this information. Hunt-
ing bag records from Germany were obtained from the
homepage of the Deutscher Jagdschutz Verband at http://
www.jagd-online.de.
Weather data
Data on precipitation and temperature for The Netherlands
were available from the Royal National Meteorological
Institute (www.knmi.nl). Data for Germany were available
from the Deutscher Wetterdienst (www.dwd.de). For analy-
sis, we averaged the freely available weather data from all
meteorological stations (in total, n054) within each county.
On average, data from 2.1 ± 0.3 SE (min, 1; max, 8) stations
per county were used. We excluded data from stations
situated higher that 1,000 m asl since the abundance of the
two study species in such regions is low. We used averaged
data per county since we only had access to summed-up
annual hunting bags from each county but not to detailed
information about the local origin of the hunting bag records
on a finer scale.
The weather variables repeatedly measured during the
years of study differed significantly among counties with
respect to temperature in spring (F
25,636
012.26, p<0.001), late
summer/autumn (F
25,636
09.13, p<0.001) and winter (F
25,636
0
12.29, p<0.001) and precipitation in spring (F
25,636
05.11, p<
0.001), late summer/autumn (F
25,636
07.55, p<0.001) and win-
ter (F
25,636
07.13, p<0.001). Furthermore, the average range
spans (maxmin) of the different weather variables provided
by the different meteorological stations within different
counties were lower than the range spans calculated among
the averaged values of the counties. Exemplarily shown here
for the year 2000, this could be observed with respect to
temperatures in spring (averaged ΔT
within counties
01.1 °C±0.2
SE; ΔT
among counties
03.2 °C), late summer/autumn (averaged
ΔT
within counties
01.0 °C±0.2 SE; ΔT
among counties
03.1 °C) and
winter (averaged ΔT
within counties
01.4 °C±0.2 SE; ΔT
among
counties
04.7 °C) and also with respect to precipitation in spring
(averaged ΔP
within counties
022.0 mm/month ± 6.9 SE; ΔP
among
counties
059.7 mm/month), late summer/autumn (averaged
ΔP
within counties
019.5 mm/month± 3.6 SE; ΔP
among counties
0
49.4 mm/month) and winter (averaged ΔP
within counties
0
24.6 mm/month±6.0 SE; ΔP
among counties
070.4 mm/month).
Model outline
The aim of the paper was to test the effects of different
weather factors on population dynamics of rabbits and hares
as assessed by within-county variation of hunting bags. For
analysis, we z-transformed the hunting bags within each
county, i.e. the number of animals shot per area where
hunting was permitted. For this, the mean number of ani-
mals shot in each county was set to zero and the deviation
from the mean (given as the number of standard deviations
within each county) was calculated for every year. For
example, a value of 2 (see Fig. 2) means that the hunting
bag in this particular year and county was two standard
deviations higher with respect to the mean of all hunting
bag records from this particular county, averaged over the
whole study period. This was done in order to avoid biases
caused by the very high differences in hare densities among
the different counties.
Weather variables were calculated by first averaging the
values of all available weather stations per county (see
above) and then by calculating values for each time window
as given in Fig. 1. Temperatures represent averaged daily
temperature means. Daily measurements of precipitation
were summed up over the respective time window and, in
order to scale them to a comparable unit, are given as
millimetre precipitation per week. Note that we repeated
our analyses using data on minimum and maximum temper-
atures and amounts of precipitation of each time window
and obtained similar results.
Statistical analysis
Analyses were done with multivariate models (linear mixed
effects models) using the statistic software R version 2.10.1
(R Development Core Team 2011). For this, we used lme4
Eur J Wildl Res (2012) 58:923932 925
package (Bates 2005). County was included as a ran-
dom factor in order to adjust for the repeated measure-
ments. The programme R does not directly provide p-
values for mixed-effects models calculated with lme4.
Thus, for the final models, we extracted the p-values
and also the parameter estimates by Markov-chain Mon-
te Carlo sampling based on 10,000 simulation runs
(Baayen et al. 2008).
For model selection, we first stepwise increased complex-
ity by including higher-order polynomials (including their
interactions with the factor country) in order to capture the
long-term dynamics of the time series of both species. We
stopped when the inclusion of a higher-order polynomial
exceeded the level of significance α00.05 using likelihood
ratio tests (Faraway 2006). We then included all weather
variables (Fig. 1) and their interactions according to our a
priori hypotheses. We considered all two-way interactions
between temperature and precipitation within the same season
and between weather conditions during the vegetation period
and conditions during the following winter. Higher-level inter-
actions were not considered in order to avoid excessive over-
parameterisation of the models. We also considered optimum
curves (quadratic effects) of precipitation in order to test the
hypothesis whether medium amounts of precipitation were
most advantageous for survival and reproduction of rabbits
and hares (Tablado et al. 2012). However, such effects were
not significant. We then stepwise reduced all predictors and
interaction terms to those with p>0.10. The significance of all
higher-order polynomials were re-checked for the final mod-
els. In addition, we calculated NagelkerkespseudoR
2
based
on maximum likelihood estimates (Nagelkerke 1991). This
was done for the final models including all significant predic-
tor variables and can be interpreted as the proportion of
explained variance.
Normality of the model residuals of the global models
as well as of the final models was assured by visually
checking normal probability plots and by performing
ShapiroWilk tests, and we assured the homogeneity of
variances and goodness of fit by plotting residuals versus
fitted values (Faraway 2006). We also checked for multi-
collinearities among the different weather variables used
in the models. The variation inflation factors calculated
for all predictor variables used in the models for rabbits as
well as for hares were always smaller than 3, indicating
no notable problems with multi-collinearities (Fox and
Monette 1992).
Results
European rabbits
Annual variation in European rabbit hunting bags in Ger-
many and The Netherlands was significantly described by a
fifth-order polynomial, including an interaction between
year and country. Generally, the time course in this species
showed a clear decreasing tendency (Fig. 2a).
Given the detected long-term trends in rabbits hunting
bags, the number of rabbits shot was lower when precip-
itationinspring(MarchtoendofMay)ofthecurrentyear
was high (Table 1;Fig.3b). In addition, our results
support the longer-term effects of precipitation in spring
on rabbit dynamics, but these have a very different effect
in interaction with the temperature conditions of the pre-
vious winter. The number of rabbits shot was lower after
harsh winters with low temperatures but only when the
precipitation in spring of the previous year was high
(Table 1;Fig.3a). The variation explained by the final model
Fig. 1 Schema of the variables
used for statistical modelling.
Asterisk, in case of crop
damage, rabbits in the
Netherlands can be shot any
time during the year. Two
asterisks, rabbits in Germany
can be shot all year round, but
in some counties breeding
animals must not be hunted
during the reproductive season
(three asterisks). The hunting
season of European hares
differs slightly among counties
in Germany. Hunting of
European hares is prohibited in
Berlin; however, this county
was excluded from the analysis
926 Eur J Wildl Res (2012) 58:923932
including all significant predictor variables was R
Nagelkerke
2
0
0.659.
European hares
The temporal variation in European hares shot was
significantly explained by a second-order polynomial
with a general tendency of a slight decrease during the
period of study. For the hare also, the model included
an interaction between year and country with a converse
U-shaped pattern in the two countries (Fig. 2b). How-
ever, the variation explained by the model was rather
moderate with R
Nagelkerke
2
00.247.
The number of hares shot was lower in years with more
precipitation in autumn/late summer, i.e. from August until
end of October (Table 1; Fig. 3c). Other weather variables or
interactions among them were not significant.
Discussion
Our results provide evidence for the impact of weather
conditions on the population dynamics of both study species
as assessed by hunting bag records. The number of Europe-
an hares shot was lower in years with higher amounts of
precipitation during late summer/autumn, and the number of
European rabbits was lower in years with high precipitation
in spring of the respective year. In addition, we found
support for our third hypothesis concerning potential inter-
actions among weather conditions between different
Fig. 2 Time series of the z-
transformed hunting bag data
(per county) of aEuropean
rabbits and bEuropean hares in
the Netherlands (open circles,
solid regression line) and Ger-
many (filled circles,dashed re-
gression line). For calculation
of the regression lines (based on
the parameter estimates of the
models given in Table 1), all
other predictor variables of the
respective models were set
constant to their means
Eur J Wildl Res (2012) 58:923932 927
seasons: There was a time-delayed, interactive effect be-
tween precipitation in spring and winter weather on Euro-
pean rabbit dynamics. Rabbit numbers were limited by low
temperatures of the prior winter season, but only when
precipitation during spring of the previous year was high.
These weather effects were detectable when stripping
offthe long-term trends in rabbit and hare hunting bags.
Both species showed the tendency of a general decrease in
numbers over the study period (Fig. 2). This trend showed a
rather high variation in the hare with quite different patterns
Table 1 Linear mixed models
on the effects of different
weather variables on the z-
transformed number of (a) Eu-
ropean rabbits and (b) European
hares shot in 26 different
counties (Nper hunting area and
year) of the Netherlands (1980
2007) and Germany (1982
2007). County was included as a
random factor. P-values and pa-
rameter estimates (including
95 % confidence intervals) were
calculated by 10,000 Markov-
chain Monte Carlo simulation
runs. Non-significant interac-
tions and higher-order polyno-
mials (p
MCMC
> 0.10) were
omitted before re-calculating the
models. A further backward
elimination of non-significant
predictors (not shown) did not
lead to different results than
those obtained by calculating p-
values for the models including
all effects shown below
Predictor variables Estimate 95 % lower 95 % upper p
MCMC
Rabbit Country 0.386 0.042 0.816 0.09
T
winter
0.077 0.176 0.018 0.11
P
winter
0.001 0.004 0.003 0.75
T
springthis.year
0.038 0.020 0.096 0.20
T
springlast.year
0.023 0.027 0.074 0.37
P
springthis.year
0.004 0.007 0.001 0.011
P
springlast.year
0.006 0.011 0.001 0.013
P
summer/autumnthis.year
0.001 0.002 0.003 0.83
P
summer/autumnlast.year
0.001 0.004 0.001 0.30
T
springlast.year
×T
winter
0.002 0.001 0.004 0.016
Year+year
2
+year
3
+year
4
+year
5
<0.001
(Year+year
2
) × country 0.026
Hare Country 2.456 3.038 1.862 <0.001
T
winter
0.001 0.053 0.053 0.98
P
winter
0.001 0.004 0.004 0.97
T
springthis.year
0.017 0.064 0.099 0.70
T
springlast.year
0.005 0.075 0.063 0.89
P
springthis.year
0.001 0.005 0.004 0.84
P
springlast.year
0.001 0.004 0.005 0.95
P
summer/autumnthis.year
0.005 0.008 0.001 0.004
P
summer/autumnlast.year
0.002 0.005 0.002 0.31
Year+year
2
<0.001
(Year+year
2
) × country <0.001
Fig. 3 Model graphs on the effects of different weather variables on the
z-transformed hunting bag of European rabbits (a,b) and European hares
(c) based on the results of the statistical models given in Table 1.For
calculation of the predicted values, all other predictor variables of the
respective models were set constant to their means. The dashed lines in b
and cshow the 95 % confidence intervals of the regression lines
928 Eur J Wildl Res (2012) 58:923932
in the two countries studied here, whereas the z-transformed
dynamics of rabbits showed a clear and distinct pattern. This
might be well explained by the fact that European rabbit
dynamics during the last decades was mainly driven by the
diseases myxomatosis and RHD (Moreno et al. 2007;
Delibes-Mateos et al. 2009) and obviously in a very similar
pattern within the different counties of The Netherlands and
Germany. Long-term dynamics of the European hare
appeared more diffuse, including a much higher variation
among the different counties, pointing towards the com-
plex interaction of various factors to be involved here
(Smith et al. 2005).
The interactive effect of the amount of precipitation in
spring and temperature conditions of the following winter
season on European rabbit numbers confirms our hypothe-
sis, mainly inferred from the results of our field enclosure
study on European rabbits (see Rödel et al. 2004a). In that
study, it has been proposed that young animals, which were
exposed to a higher amount of rain, might have to carry
higher costs for thermoregulation (cf. Seltmann et al. 2009)
and might have a higher chance to get infected with dis-
eases. In particular, rain and humidity are known to favour
the spread of endoparasites (e.g. nematodes and coccidia) by
increasing the persistence of infective stages outside the
body of the host (O'Connor et al. 2006; Stromberg 1997).
Especially in younger animals, such infections cause mor-
tality (Broekhuizen and Mulder 1983), but these mecha-
nisms can also together result in lowering the body
condition of the animals and thus drive the negative corre-
lation between rainy weather conditions and growth (Rödel
and von Holst 2008). In turn, such animals suffering from
stunted growth and from high endoparasite burden will then
be more susceptible to low winter temperatures since
disease-induced mortality can be enhanced by cold stress
(Kelley 1980). Furthermore, low winter temperatures do not
only have the potential to directly act on body condition and
survival of the animals by means of increasing thermal
stress and the costs of thermoregulation but can also be
considered as a proxy of availability or quality of food
(Rödel 2005). We think that it is most likely that these
mechanisms were important drivers of the here observed
limiting and interacting effects of spring precipitation and
winter temperature conditions on rabbit hunting bags.
Nevertheless, other explanations not mutually exclusive
might be considered. For example, effects of predation may
also contribute in shaping the weather-driven dynamics, as it
was apparent in European rabbits. Predators, such as foxes
and mustelids, might switch to rabbits as alternative prey to
a higher extent when small rodentsdensities are low due to
cold winters or high amounts of rain in spring, causing
flooding and thus high mortality rates in mice and voles.
The limiting effects of rain and flooding of breeding bur-
rows on offspring survival are also well known in the
European rabbit (Palomares 2003; Rödel et al. 2009a) and
might explain the direct negative effect of spring precipita-
tion on rabbit numbers. Another possible explanation for
limiting effects of low winter temperatures on rabbit numb-
ers rests on effects on the onset of the annual reproductive
season. For example, a delay in the onset of breeding after
harsh winters has been reported for several lagomorph spe-
cies (Rogowitz 1992; Wright and Conaway 1961; European
rabbit: Bell and Webb 1991; Rödel et al. 2005). A later onset
of breeding limits the number of progeny born early in the
season, and early born offspring (at least the ones surviving
the early juvenile period) usually have higher chances to
survive during the first winter than individuals born later
since they enjoy a longer time during the vegetation period
for growth prior to the winter (Kraus et al. 2005; Feder et al.
2008; European rabbits: Rödel et al. 2009b). Surely, day
length also plays a role in triggering the onset of breeding in
the European rabbit (Hudson et al. 1994), but such effects
are strongly modified by environmental conditions. On the
other hand, and in accordance to our results, the influence of
weather conditions on the onset of breeding in the European
hare appears to be low, whereas triggering by day length is of
significant importance (Frylestam 1980)although the length
of the breeding season has been reported to be extended by
mild autumn conditions (Hewson and Taylor 1975).
In our study, weather effects on European hares were
only apparent in summer/autumn, indicating the limiting
effects of high amounts of rain on hare densities at this time
of the year. This result fits very well to the findings of other
reports on European hares showing major influences of
weather conditions particularly during the summer months
(Nyenhuis 1995) and pointing towards a higher importance
of rainy weather conditions in comparison to temperatures
(Smith et al. 2005; van Wieren et al. 2006). We propose that
also here, a higher rate of infection by diseases in areas and
years with rainy and wet weather conditions might be the
main driver for the observed precipitation effects in summer
and autumn. Higher metabolic costs in wet, unfavourable
environments, in particular in young animals (Seltmann et
al. 2009; Hackländer et al. 2002), may restrict the allocation
of energy to other physiological functions such as to the
animalsimmune defence (Muehlenbein et al. 2010), thus
favouring the outbreak of diseases. On the other hand, it
cannot be fully ruled out that there might be also a bias
caused by the limiting effects of harsh weather conditions
(i.e. high precipitation) on hunting effort, thus potentially
affecting hunting bag records.
When comparing both study species, there were appar-
ently stronger effects of weather on rabbit than on hare
population dynamics (a) by means of the higher number of
correlations observed on different levels and (b) due to the
higher effect sizes of the observed effects. In the rabbit, the
estimated effect size of the interaction model varies by about
Eur J Wildl Res (2012) 58:923932 929
1 standard deviation around the population average
(Fig. 3a), whereas the slope of the regression line in the
hare only varies by around 0.5 standard deviation (Fig. 3c).
At first sight, this seems surprising because, in comparison
to the precocial hare, rabbits are born and raised in the
shelter of a breeding burrows dug by the mother. However,
European hares might be better adapted to the climatic
conditions of Central Europes temperate zone habitats (cf.
Hackländer et al. 2011) than the European rabbit, which
mainly evolved in the climate of the Iberian Peninsular
and of which Germany and The Netherlands are in the most
northern part of its range (Thompson and King 1994).
Furthermore, it remains open whether the here observed
effects influence the two study species in a similar way in
other climate zones within their distribution range.
It has to be noted that the methodological approach of
our study may affect the interpretation of the results.
First, drawing conclusions on population dynamics based
on hunting bags has been often criticised, and hunting
itself might directly affect the population dynamics of a
species (Besnarda et al. 2010; Willebrand et al. 2011;
Williams et al. 2007). However, some confirmation on
the appropriateness of the use of hunting bags as an
estimate for population biology studies comes from the
fact that hare and rabbit hunting bags of the Netherlands
correlate strongly and positively with the (10 years
shorter) time series of data collected by systematic visual
daylight counts (R
2
00.90 for hare and R
2
00.82 for rab-
bit; JJAD, unpublished data). Second, we are aware that
variation in weather conditions on a local scale was only
moderately captured by our method of averaging data
from several meteorological stations per county. Thus,
we conclude that this studys negative, non-significant
results should be interpreted with some caution. We
cannot deny that, e.g., winter weather effects may well
be involved in the dynamics of European hares (see
Marboutin and Hansen (1998); Smith et al. 2005;Tkadlec
et al. 2006) as we might have overseen smaller effects
with our conservative approach. Therefore, we would have
rather underestimated than overestimated the effects of
weather conditions on the population dynamics of the two
species studied. As a consequence, we propose that the
positive results of our study are of significant importance
since we managed to detect them despite our conservative
approach.
In conclusion, the study clearly shows the impact of
weather factors on the dynamics of the two species studied.
In particular, the results highlight the importance of the time-
delayed interaction between different weather variables acting
on the animals during different seasons, and we propose that
such effects may also well occur in species other than the
European rabbit. Thus, our findings might have important
implications for the understanding of the effects of density-
independent factors on animal populations and may help to
predict potential consequences of climate change.
Acknowledgments We are grateful to the Koninklijke Nederlandse
Jagersvereniging, in particular to Dr. Montizaan, who kindly provided
us the data on rabbit and hare hunting bags in The Netherlands and to
Deutscher Jagdschutzverband, in particular to Ms. Ayed, who kindly
provided us data on the size of hunting areas in Germany. Thanks also
to A. Punt and to F. Locke for their social support.
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Assessing the underlying mechanisms of co-occurrence patterns can be challenging as biotic and abiotic causations are hard to disentangle. To date, few studies have investigated co-occurrence patterns within urban areas that constitute novel habitat to numerous wildlife species. Moreover, as urban areas expand and are increasingly used as habitat by wildlife, there is a need for a better understanding of urban ecology to facilitate human-wildlife coexistence. Here, we investigated co-occurrence patterns and habitat selection of the European hare (Lepus europaeus), mountain hare (L. timidus), and European rabbit (Oryctolagus cuniculus) inside urban areas of Sweden, using joint species distribution models and generalized linear mixed models based on citizen science observations. All three species were observed within urban areas, but European hares and rabbits appear to be more successful urban colonizers compared to mountain hares. Overall, our findings suggested that urban occurrence by all three lagomorphs was related to suitable conditions within the distribution of each species (e.g. climate and elevation), rather than by the presence of other lagomorph species or specific land cover types within urban areas. On a finer spatial scale, our findings suggested facilitation of European hares by rabbits, though the mechanism for this remains unclear. European hares and rabbits generally selected for green urban areas and mountain hares for residential gardens, which likely constitute suitable foraging sites. Our findings contribute to the understanding of urban ecology and provide valuable insight for management measures of the three lagomorphs in urban areas of Sweden.
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We evaluated the relationship between growing-season phenology, as indicated by time of snow melt, and intrapopulation variation in reproduction and growth of yellow-bellied marmots. The time of snow melt explained significant proportions of the variation in frequency of reproduction (78%), litter size (79%), and estimated body mass of young of the year (68%), but not growth rate. We suggest that the duration of snow cover, through its effect on the length of the growing season, influences habitat quality; marmots living at localities with prolonged snow cover have a shorter season of access to food. The variation in life-history traits is attributed to phenotypic plasticity and not to local genetic variation.
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Radio equipped roe deer were located each week during a mild winter with shallow snow depth (1975-76) and a severe winter with snow depth >100 cm (1976-77). Daily mean home range of males was about the same in the 2 seasons with small variations between 4-wk periods (1975-76 mean 19.0 ha and 1976-77 mean 20.6 ha). Females, however, responded to increased snow depth in 1976-77 and covered the smallest daily ranges at snow maximum in the weeks 05-08 and 09-12 (7.7 ha and 8.9 respectively) while in 1975-76 no such behaviour was noticed (1975-76 mean 20.5 ha; 1976-77 mean 11.9 ha) . Extremely small daily mean home ranges were more frequent in 1976- 77 than in 1975-76, 45% and 20% of total sample respectively being smaller than 10 ha. The total winter home range was extended into a wider area in 1976-77. Male roe deer seemed to be more disposed to move from summer range to feeding sites than females.-from Author
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Reynolds, J.C. & Tapper S.C. 1995: Predation by foxes Vulpes vulpes on brown hares Lepus europaeus in central southern England, and its potential impact on annual population growth. - Wildl. Biol. 1: 145-158. A computer model was used to simulate processes of reproduction. growth and loss occurring during twelve months within a real-world brown hare Lepus europaeus L. population in a mixed farming area of central southern England. Model parameters representing hare density, and the density and diet of foxes Vulpes vulpes L., were derived from field studies, whereas likely values for other parameters were set on the basis of studies performed elsewhere. Simulations were created to represent a) the hare population on an area of 11 km: comprising several fox territories; and b) the hare population on individual fox territories. In the larger-scale simulations (a), the number of hares eaten by foxes easily exceeded their breeding density and amounted to 76-100% of annual production. The hare population could not have withstood more than a very low additional mortality without declining. When fox predation was set to zero, the final density of hares in the model was 3 to 6 times that produced when fox predation occurred. Simulations for individual fox territories (b) suggested that variation in territory size and social group composition of foxes introduced significant local variation within this overall picture. We conclude that the hares eaten by foxes were a substantial loss relative to productivity. This conclusion was robust in the face of estimation errors or changes in underlying assumptions of the model. This study describes the extent of fox predation on hares and its potential impact on hare population growth. Because the degree of compensation between mortality factors was unknown, the study does not show that fox predation per se limited the hare population. Nevertheless, our findings are a necessary adjunct to experimental evidence and population studies which suggest that red foxes play a major role in hare population dynamics in many environments.
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In 1999 brown hares were counted using the headlight method (PEGEL 1986) during the course of two counting periods (end of February to mid April; beginning of October to mid November with occasional counts continuing into December). 305 districts from 56 Bavarian counties participated in the counts. The population densities of Brown hares determined from the counts varied between 3 and 83 hares per sq. km (of total areas counted) in the spring and between 1.2 and 147.4 hares per sq. km in the fall. The highest densities were determined for the natural areas in Maintal, Mittelfränkisches Becken, Frankenhöhe, Nördlinger Ries, Dungau, and Unteres Inntal. The evaluation of data from the individual districts that have been conducting counts of brown hares since 1996 shows a steady increase in the base population in the spring. With the aid of statistical analyses positive correlations between the density of field hares and various complexes of factors were determined. Accordingly, the density of hares increases with favourable climate, the proportion of agriculturally used areas, particularly grain fields, as well as with greater diversity and natural breaks within fields. Further conclusions pertaining to land use can be made when all data have been compiled.
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The main differences in nursing behaviour between Lepus and Oryctolagus cuniculus concern the period during which young rabbits stay in stopped breeding burrows; after emerging rabbit behaviour is very similar to that in hares.-from Authors
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