Download WINTER BROWSING BY MOOSE AND HARES IN SUBARCTIC

Thesis for the degree of Doctor of Philosophy, Sundsvall 2015
WINTER BROWSING BY MOOSE AND HARES IN SUBARCTIC
BIRCH FOREST – SCALE DEPENDENCY AND RESPONSES TO
FOOD ADDITION
Sara M. Öhmark
Supervisors:
Professor R. Thomas Palo
Professor Glenn R. Iason
Professor Bengt-Gunnar Jonsson
Faculty of Science, Technology, and Media
Mid Sweden University, SE-851 70 Sundsvall, Sweden
ISSN 1652-893X
Mid Sweden University Doctoral Thesis 229
ISBN 978-91-88025-38-8
Akademisk avhandling som med tillstånd av Mittuniversitetet i Sundsvall
framläggs till offentlig granskning för avläggande av filosofie doktorsexamen i
biologi, fredagen den 2 oktober 2015, klockan 10.15 i sal O102, Mittuniversitetet
Sundsvall.
Seminariet kommer att hållas på engelska.
WINTER BROWSING BY MOOSE AND HARES IN SUBARCTIC
BIRCH FOREST – SCALE DEPENDENCY AND RESPONSES TO
FOOD ADDITION
Sara M. Öhmark
© Sara M. Öhmark, 2015
Department of Natural Sciences, Faculty of Science, Technology, and Media
Mid Sweden University, SE-851 70 Sundsvall
Sweden
Telephone:
+46 (0)10-142 80 00
Printed by Mid Sweden University, Sundsvall, Sweden, 2015
“…whilst this planet has gone cycling on according to the fixed law of gravity, from
so simple a beginning endless forms most beautiful and most wonderful have been,
and are being, evolved.”
-Charles Darwin, The Origin of Species
Till min familj
Lyckan, i alla dess oändliga former,
finner jag varje dag i er.
WINTER BROWSING BY MOOSE AND HARES IN SUBARCTIC
BIRCH FOREST – SCALE DEPENDENCY AND RESPONSES TO
FOOD ADDITION
Sara M. Öhmark
Department of Natural Sciences
Mid Sweden University, SE-851 70 Sundsvall, Sweden
ISSN 1652-893X, Mid Sweden University Doctoral Thesis 229;
ISBN 978-91-88025-38-8
ABSTRACT
Despite their difference in body size and morphology, the moose (Alces alces) and
the mountain hare (Lepus timidus) sustain themselves during winter on similar plant
species and plant parts in in subarctic environments, namely apical twigs of
mountain birch (Betula pubescens ssp. czerepanovii). Herbivores must select areas and
items of food that provide sufficient intake rates and food nutritional quality while
balancing this against their intake of dietary fiber and potentially detrimental plant
secondary metabolites. This selection takes place simultaneously at multiple spatial
scales, from individual plants and plant parts to patches of food and parts of the
wider landscape. While the herbivores must consider their need for food to sustain
daily activities, for body growth and reproduction it is also necessary to avoid
predators and harsh environmental conditions. For managers, an understanding of
key factors for animal foraging distributions is pivotal to reach intended goals of
management and conservation plans. Knowledge in this area is also important for
models to make accurate predictions of foraging responses of herbivores to resource
distributions. The mountain birch forest displays a naturally heterogeneous
distribution of trees and shrubs which presents herbivores with a challenge to find
good feeding areas. In an investigation of the spatial distribution of moose browsing
on birch and willows (Salix spp.) in two winter seasons separated in time by 14 years,
it was found that moose browsing patterns in 1996 were correlated to those observed
in 2010. It was also found that moose browsing was spatially clustered within the
same distances (1000-2500 m) as densities of willow and birch, but at other spatial
i
scales, browsing was mostly randomly distributed. It was concluded that forage
density is a cue for moose but only at certain spatial scales. Similarly, a comparison
of foraging distribution by hare and moose showed that high birch density was a
key factor for both species. In spite of this, hares and moose used different parts of
the same environment because they respond to food resource distribution at
different spatial scales. Hares fed from smaller plants, and focused their foraging
activity on smaller spatial scales than moose. These results emphasize the
importance of taking into account the distribution of food resources at spatial scales
relevant for each species in plans for conservation and management. In an
experimental study it was found that intensified browsing on natural forage by
mountain hares can be induced locally through placement of food. The induced
browsing varied with the amount and quality of the added food, but also with the
density of natural food plants and natural foraging distribution by hares. Finally, in
a last experiment habitat preference of mountain hares across edges between open
and forested areas was studied. The results were not consistent; hares utilized bait
to a greater extent within forested areas than bait placed on a nearby lake ice, but
bait on mires and heaths was either preferred over bait in nearby forest, or utilized
to a similar extent. A possible explanation is that hares have knowledge of their
environment such that both forested areas and subarctic mires and heaths are part
of its natural home range, whilst the extreme environment on the lake ice is not.
During recent decades arctic areas have had an increase in vegetation density and
will be affected by future climate warming and therefore, factors that determine
foraging ecology of key herbivores need to be identified. This thesis sheds some light
on these factors in relation to spatial scale and forage distribution for two high
profile herbivores in the subarctic.
Keywords: foraging distribution, moose (Alces alces), mountain birch (Betula
pubescens sp. czerepanovii), willow (Salix spp.), spatial scale, niche separation,
supplementary feeding, edge effects
ii
SAMMANDRAG
Skogshare (Lepus timidus) och älg (Alces alces) lever under vintertid i huvudsak
av kvist från träd och buskar i subarktisk fjällbjörkskog (Betula pubescens ssp.
czerepanovii) och delar alltså samma födokälla trots skillnader i storlek och
morfologi. För att tillgodose sina näringsbehov måste växtätare välja de områden
och de plantor som ger tillräckliga mängder mat av tillräckligt god näringsmässig
kvalitet. Samtidigt måste de balansera detta mot intaget av fibrer och potentiellt
skadliga sekundära metabiloter i växterna. Dessa val sker på flera rumsliga
skalnivåer samtidigt; från valet av individuell växt och växtdelar, till grupper av
växter och delar av landskap. Växtätaren behöver även balansera sitt behov av mat
med andra prioriteter, som att undvika rovdjur och söka möjlighet att föröka sig.
För att uppnå avsedda mål för skötsel- och bevarandeåtgärder, är det nödvändigt
att förstå växtätares respons på fördelning av resurser. Kunskap inom detta område
är även viktigt för att i modeller kunna göra tillförlitliga prediktioner av växtätares
födosöksmönster. Fjällbjörkskogen uppvisar naturligt en fläckvis utbredning, vilket
innebär en utmaning för växtätare som söker områden med god tillgång till föda.
Den rumsliga fördelningen av älgbete på fjällbjörk och viden undersöktes under två
vintersäsonger med 14 års mellanrum (Salix spp.) och det visades att älgens
betesmönster under 1996 var positivt korrelerat till det som observerades under
2010. Älgbetet var koncentrerat inom samma distanser (1000-2500 m) som densiteten
av vide och björk, medan älgbetet sett över andra rumsliga skalor var slumpvis
fördelat. En slutsats av dessa resultat är att densiteten av födoväxter styr älgens
födosöksmönster, men bara inom vissa rumsliga skalnivåer. En jämförelse av
betesfördelning mellan hare och älg visade på ett liknande sätt att hög densitet av
björk var avgörande för födosöksmönstren hos båda arterna. Trots detta var det
uppenbart att hare och älg utnyttjar olika delar av samma områden eftersom de
reagerar på fördelningen av resurser på olika rumsliga skalnivåer. Harar betade från
mindre björkar och fokuserade sitt bete inom mindre rumsliga skalor jämfört med
älg. Dessa resultat belyser vikten av att se till fördelningen av födoresurser på de
skalnivåer som är relevanta för respektive art vid planering och utförande av
skötsel- och bevarandeåtgärder. I en experimentell studie befanns det att ökat
harbete på naturlig vegetation kan framkallas lokalt genom utplacering av foder.
Det ökade betet varierade med mängd och kvalitet av det utplacerade fodret, men
det berodde även på tätheten hos björkskogen på foderplatser samt på den naturliga
distributionen av harbete på björk. Slutligen, i en sista studie undersöktes harens
preferens för olika miljöer där fjällbjörkskog angränsar till öppna ytor. Hararnas
iii
respons till utplacerat foder i öppen terräng jämfört med i fjällbjörkskog var inte
konsekvent. Hararna undvek sjöis men visade antingen en positiv eller en neutral
respons till foder placerat på subarktiska myrar eller hedar, jämfört med foder
placerat i fjällbjörkskog. En möjlig förklaring till detta är att hararna känner till
miljön inom sina hemområden som innefattar både fjällbjörkskog och subarktiska
hedar och myrar medan sjöisen inte utgör ett habitat för haren. Under senare
decennier har en ökad tillväxt av träd och buskar observerats i arktiska områden,
och dessa områden förväntas påverkas särskilt starkt av ett allt varmare klimat även
i framtiden. Därför är det relevant att identifiera de faktorer som är avgörande för
födosök och födointag hos växtätare. Denna avhandling belyser dessa faktorer i
relation till rumsliga skalor och fördelningen av bete för två växtätare som har stor
påverkan på subarktisk miljö.
iv
TABLE OF CONTENTS
ABSTRACT ......................................................................................................................... I
SAMMANDRAG ............................................................................................................ III
TABLE OF CONTENTS .................................................................................................. V
LIST OF PAPERS ............................................................................................................ VI
1.
INTRODUCTION ......................................................................................................1
1.1.
THESIS BACKGROUND .............................................................................................1
1.2.
PLANTS AS A FOOD RESOURCE ................................................................................1
1.3.
STUDY SPECIES .......................................................................................................4
1.3.1.
Mountain hare (Lepus timidus) ......................................................................5
1.3.2.
Moose (Alces alces) ........................................................................................6
1.4. HARE AND MOOSE IN MOUNTAIN BIRCH FOREST......................................................7
1.5.
CONSEQUENCES OF CONTRASTING BODY SIZES .......................................................9
1.6.
FORAGING MODELS/OPTIMALITY MODELS ............................................................. 10
1.7.
SCALE DEPENDENCE.............................................................................................. 11
1.8.
EDGE EFFECTS ....................................................................................................... 13
1.9.
BAITING AND SUPPLEMENTARY FEEDING OF WILD HERBIVORES ........................... 14
2.
OBJECTIVES ............................................................................................................. 15
3.
METHODS ................................................................................................................ 16
3.1.
3.2.
3.3.
3.4.
4.
STUDY AREA ........................................................................................................ 16
DATA COLLECTION................................................................................................ 19
RESPONSE VARIABLES ........................................................................................... 20
DESIGN OF SAMPLE PLOTS ..................................................................................... 21
RESULTS AND DISCUSSION ............................................................................. 23
4.1.
4.2.
4.3.
4.4.
PAPER I ................................................................................................................. 23
PAPER II ................................................................................................................ 24
PAPER III............................................................................................................... 25
PAPER IV .............................................................................................................. 26
5.
CONCLUSIONS ....................................................................................................... 27
6.
ACKNOWLEDGEMENTS ..................................................................................... 28
7.
REFERENCES ........................................................................................................... 30
v
LIST OF PAPERS
This thesis is mainly based on the following four papers, herein referred to by their
Roman numerals:
Paper I
Distribution of winter browsing by moose: evidence of long-term
stability in northern Sweden
R. Thomas Palo, Sara M. Öhmark, and Glenn R. Iason, 2015, Alces 51,
35-43
Paper II
Spatially segregated foraging patterns of moose (Alces alces) and
mountain hare (Lepus timidus) in a subarctic landscape: different
tables in the same restaurant?
Sara M. Öhmark, Glenn R. Iason, and R. Thomas Palo, 2015, Canadian
Journal of Zoology 93, 391-396
Paper III
Artificially added forage for wild mountain hares (Lepus timidus)
increases browsing on surrounding mountain birch (Betula
pubescens ssp. czerepanovii)
Sara M. Öhmark, R. Thomas Palo, and Glenn R. Iason, manuscript,
submitted to Journal of Wildlife Management
Paper IV
The influence of mountain birch (Betula pubescens ssp.
czerepanovii) forest cover and distance from forest edges on
utilization of added food by mountain hares (Lepus timidus) in a
natural forest mosaic
Sara M. Öhmark, Glenn R. Iason, and R. Thomas Palo, manuscript
Paper I and II were reprinted with kind permission from the journal Alces and NRC
Research Press.
vi
1.
INTRODUCTION
1.1.
Thesis background
For foraging herbivores, food quantity and quality determine the choice of foraging
area, the time the animal stays within the area and the rate of forage intake (Brown
1988; Searle et al. 2005; Ungar & Noy-Meir 1988). During winter, browsers in boreal
environments are mainly restricted to a diet of woody plant parts, which are low in
nutrients and high in fibers and secondary metabolites (Rousi et al. 1991; Palo et al.
1992; Nordengren et al. 2003). By altering e.g., movement rates, bite size and site
selection, animals can improve their chances to maintain sufficient intake of energy
and nutrients as they move through heterogeneous environments (Demment &
Greenwood 1988). There is a broad range of physiological and morphological
adaptations to herbivory among animals, such as the complex digestive system
among ruminants (Hofmann 1989). Behavioral adaptations might not be as readily
identified and interpreted as morphological or physiological ones since free living
animals are often difficult to observe in nature, but behavior and physiological
function are closely related (Van Soest 1996; Laca et al. 2010). Spatial distribution
and habitat use by animals is often well described (Cederlund & Sand 1994; Hulbert
et al. 1996; Kauhala et al. 2005; Dussault et al. 2005). However, the multitude of
factors that influence animal utilization of resources means that it is a challenge to
define and understand the underlying causes of their spatial distribution and
foraging patterns (Owen-Smith et al. 2010; Stolter et al. 2005). This thesis addresses
the response of herbivores to natural and artificial distribution of forage in a
subarctic mountain birch (Betula pubescens ssp. czerepanovii) forest environment in
northern Sweden. The hypothesis that herbivores seek the best habitats as measured
in the quality and amount of food was tested in a series of experiments and
observations on moose (Alces alces) and mountain hare (Lepus timidus), to reveal
factors that affect the distribution of these animals.
1.2. Plants as a food resource
While a carnivore’s diet fulfills basic dietary needs with nutritional components
that are easily extracted, herbivores face a food source that is relatively poor in
nutrient content and partly indigestible (Iason & Van Wieren 1999; Steuer et al.
2013). With respect to qualitative issues, plant material can be divided into two
functional fractions, namely cell contents and cell walls. Cell contents are mainly
1
soluble carbohydrates and proteins that are easily digested in vertebrate stomachs
(Demment & Van Soest 1985). In contrast, cell walls mainly consist of indigestible
(lignin) and potentially digestible (cellulose, hemicelluloses) compounds (Iason &
Van Wieren 1999; Van Soest 1994). Although cell walls cannot be degraded by
vertebrate enzymes, it can be hydrolysed by microbial fermentation within
herbivore gut systems (Flint & Bayer 2008). High rates of lignified cell wall material
in the forage decrease the rate of digestion, thereby depressing nutrient value (Van
Soest 1967; Hjeljord et al. 1982). However, several classes of fibres, both digestible
and indigestible, are essential for the digestive health and function of animals
(Gidenne 2003; Van Soest 1994). The consequence of fibre content on food quality is
thus a sum of contrasting factors, and it is dependent on proportion of cell wall
material to plant content, as well as on the rate of lignification (Van Soest 1994).
Plants produce a vast array of substances that are commonly referred to as
“secondary” compounds, so called because they were earlier mostly not known to
be involved in primary processes of plant metabolism, such as protein synthesis
(Fraenkel 1959). These compounds are widely recognized as key players in
interactions between plants and animals (Palo 1984; Dearing et al. 2005; Iason 2005).
Some secondary compounds can reduce the ability of herbivores to digest food or
assimilate nutrients, while other act as toxins (Belovsky & Schmitz 1994). Defensive
compounds are generally not allocated evenly within a plant, but are concentrated
in plant parts that contribute most to plant fitness (Ballaré 2014; Zangerl & Bazzaz
1992).
As the food source of herbivores is often low in nutritional value, a high intake
rate is necessary for meeting dietary needs (Owen-Smith & Novellie 1982). However,
making up for low nutrient content in the food by high rates of ingestion is not a
solution that comes without restrictions. The digestive capacity among herbivorous
mammals for any forage depends on gut volume, intake rate and passage rate of
food (Clauss et al. 2007). The design of the digestive system is also a major
determinant for its function apart from the size of the gut. A categorization of
herbivores can be made based on the placement of the fermentation chamber. The
fermentation chamber within digestive systems of mammalian herbivores is either
situated in the rumen (foregut), or in the cecum/colon (hindgut) (Janis 1976). The
ruminant digestive system is characterized by foregut fermentation, as the rumen is
the site of microbial digestion of plant material (Van Soest 1994). Particle size
reduction in ruminants is performed by regurgitation and chewing of food that
enhances the exposure of particle surface to rumen microbes (Welch 1982; Pond et
al. 1984). The passage between the ruminoreticulum and third forestomach acts as a
bottleneck, controlling the outflow of digesta from the rumen. This function
2
prolongs the time of microbial digestion of the rumen content, but limits the rate at
which new food can be ingested (Hofmann 1989). In hindgut fermenters, particle
separation and fermentation takes place after the passage through the small
intestine, which is the primary site for absorption of nutrients (Hintz et al. 1978). To
minimize the loss of microbial protein and vitamins while managing food with high
fibre content, many hindgut fermenters, especially of small size and including
mountain hare, re-ingest the cecum content, a function called caecotrophy
(Hirakawa 2001; Pehrson 1983a). In this way, microbial nutrients are utilized rather
than lost through defecation, and this is especially important for herbivores living
on low-nutrient forages in harsh environments, such as hares (Björnhag & Snipes
1999).
A heterogenic plant dispersion is common in natural environments, whereas
homogenous distributions are often only found in managed grazing pastures, or
rarely in natural monocultures. A common way of illustrating the distribution of
forage for animals is as patches of food embedded in a matrix that is devoid of food
resources (Charnov 1976). Patches of vegetation are seldom discrete items, but
display a variable degree of contrast to the surrounding landscape matrix (Kotliar &
Wiens 1990). Such patches can be viewed as assemblies of food that are utilized by
herbivores to various extents rather than being simply emptied or killed (MacArthur
& Pianka 1966). One way to define a patch is that food items belong to the same
patch if the time to chew and swallow the food exceeds the time it takes to travel to
another patch (Spalinger & Hobbs, 1992). The spatial distribution of plants in
relation to other available forage is essential for the food selection of herbivores
(Milligan & Koricheva 2013; Bergman et al. 2005). A highly preferred plant can either
receive protection from herbivory by the association with a less preferred plant
(repellent plant-hypothesis) or by growing near an even more palatable plant
(attractant-decoy hypothesis) (Atsatt & O’Dowd 1976).
Depending on their dietary niche mammalian herbivores are categorized either as
browsers, which preferably eat from forbs, shrubs and trees or as grazers, which
preferably consume grasses (Shipley 1999; Hofmann 1989). There is also a
differentiation between generalists, which include many plant species in their diets,
and specialists, which only feed from a few plant species (Freeland & Janzen 1974;
Shipley et al. 2009). Dietary specialization of herbivores is rare, and this has been
proposed to either be due to that few plant species can satisfy all dietary demands,
or due to satiation of plant secondary compounds in a narrow diet (Dearing et al.
2000). Shipley et al. (2009) suggested that mammalian herbivores should be assigned
as either “obligate” or “facultative” specialists or generalists, to indicate the causes
for the dietary niche. The term obligate specialist or generalist should be used if
3
specialization or generalization occurs due to behavioral and/or morphological
adaptation, and for facultative specialist or generalist, the local availability of forage
forces a narrow or a broad diet. In the latter case the specialization depends on
spatial and temporal scale.
In summary, herbivores face a food source that is unevenly distributed in terms
of availability and quality and their ability to respond to this variation depends on
species- specific contraints. This forms an important part of the background of this
thesis, which focuses on the distribution of moose and hare foraging activity in
relation to food quantity and quality. The mountain hare practises caecotrophy and
particle separation in the hindgut which preferentially accelerates excretion rather
than retention of larger poorly digestible food fragments, whereas the moose
physically degrades ingested food by chewing and rumination and is likely to be
unable to respond to lower quality diets by increasing food intake due to passage
constraints in its foregut. The utilisation of food resources by these two herbivores
(paper II) is likely to be underpinned by these contrasting methods of digestive
processing.
1.3.
Study species
Figure 3.
Mountain hare (Lepus timidus) in white winter pelage. Photo by Sara Öhmark.
4
1.3.1.
Mountain hare (Lepus timidus)
The mountain hare (Figure 1) is a generalist herbivore with a capacity to rely on
food sources that are very low in nutrient content (Pehrson 1983b). It is a hindgut
fermenter that displays an intermediate feeding strategy between grazing and
browsing and it is highly flexible in diet intake (Hulbert & Andersen 2001). In winter
in Fennoscandia, the hares predominantly browse on species of birch and willow,
whereas the summer diet mainly consists of herbs (Johannessen & Samset 1994;
Pulliainen & Tunkkari 1987). If high quality food such as grass is available it is
preferred also during winter as browse material is eaten when the availability of
better-quality food is restricted (Hulbert et al. 2001). The choice of food source
among mountain hares has been suggested to depend on the digestibility, fibre
content and concentration of plant secondary compounds, rather than on nutrient
concentration in plants (Hjältén & Palo 1992).
Hares cannot rely on fat reserves during harsh periods as is common for larger
animals like the moose (Alces alces), but will instead maintain their body weight
throughout winter (Cederlund et al. 1991; Lindlöf 1980; Thomas 1987). Since hares
also have a high metabolic rate relative to larger herbivores (see section 1.5), the daily
food intake is of utmost importance. To maintain itself on a diet of twigs, a mountain
hare weighing 3.5 kg needs an intake of at least 500 g fresh twigs per day (Pehrson
1979). Caged mountain hares maintain their body weight in outdoor winter
conditions when fed on twigs from deciduous plants, including birch and willows,
with the exception for birch twigs of less than 1.5 mm in diameter (Pehrson 1983b).
Even in habitats were a single plant species is dominant, hares are able to survive
(Angerbjörn & Pehrson 1987; Hewson 1976). Under such conditions, choosing
individual plants and plant parts with high nutrient content is important for the
hares to meet their nutritional demands. In habitats with mixed vegetation, the scope
to obtain sufficient nutrient intake from a mixed diet may diminish the significance
of the nutritional quality of a single species (Angerbjörn & Pehrson 1987).
Hares are not competitive for territory, although they show high site-fidelity both
between years and between seasons (Dahl 2005). The establishment of a home range
occurs within 90 days of age for a mountain hare in northern Sweden (Dahl &
Willebrand 2005). In harsh environments with uneven distribution food, it is
essential that a home range includes sheltered resting sites and a sufficient amount
of forage (Hewson & Hinge 1990). As hares track food resources that change over
seasons, their home ranges will be focused to areas with comparatively high quality
and availability of food (Dahl 2005). Relocation of snowshoe hares has been found
to cause an increased mortality due to predation, which suggests that local
5
knowledge is important for the survival of hares (Sievert & Keith 1985). A study in
northern boreal parts of Sweden (Dahl & Willebrand 2005) and a study in boreal
Finland (Kauhala et al. 2005) gave median annual home ranges of 271 hectares, and
of 206 hectares, respectively. Results from these studies showed annual fluctuations
in home range sizes, with smaller median values during summer and autumn and
larger during winter and spring. The combination of a restricted home range size, a
high metabolism and a high food intake rate, makes the mountain hare a suitable
species for studying foraging mechanisms in response to food availability and
quality.
Figure 2.
1.3.2.
Moose (Alces alces). Photo by Sara Öhmark.
Moose (Alces alces)
The moose (Figure 2) is a large ruminant weighing 250-600 kg that typically feeds
from browse material (Cederlund et al. 1986; Wam & Hjeljord 2010). It is considered
a model species for ecological studies of a browsing ruminant (Shipley 2010) because
it occupies a wide global range, is of high recreational interest, and has high
economic and ecological impacts on its surroundings (Milligan & Koricheva 2013;
Muiruri et al. 2015; Condon & Adamowicz 1995). The moose can behave as a
generalist forager, or as a specialist depending on season and location, which has
made it difficult to define its dietary niche. Shipley et al. (2009) suggested that it
should be termed a facultative specialist, i.e., an animal that has the potential of
keeping a varied diet but that eats a narrow range of food plants of comparatively
poor nutrient value during certain times or at certain locations. Moose have a low
passage rate of fluids and small particles through their forestomach compared with
6
other large ruminants. This has been suggested to limit food choice for moose to
browse material (Lechner et al. 2010). Moose also have a long cropping time relative
to other herbivores which restricts intake rates (Shipley et al. 1994).
During summer, moose predominantly eat deciduous leaves and forbs, while its
winter food mostly consist of deciduous and coniferous twigs (Shipley et al. 1998;
Wam & Hjeljord 2010). Summer intake rates are higher than during winter, while
the rate of selectivity is higher during summer as more diverse food items are
available (Renecker & Hudson 1986). However, selectivity of food items during
winter can to some extent make up for low availability of forage (Shipley et al. 1998).
As the possibility to make selections of food types is limited in winter the animals
are confined to a restricted diet which may not support a positive energy balance
(Sæther & Gravem 1988; Moen et al. 1997). Moose are most active during sunset and
sunrise and alternate bouts of active food search with inactive bouts when the food
is processed by rumination (Cederlund & Sand 1994). During winter more time is
needed for rumination as the food contains higher amounts of fiber, while less time
is put on actively searching and ingesting food (Renecker & Hudson 1989). Daily
intake of dry matter per kilo body weight varies with age and gender of the moose,
and with forage availability (Vivås & Sæther 1987; Nyström 1980; Renecker &
Hudson 1986). Daily winter dry matter intake for moose calves in Grimsö, central
Sweden, has been estimated to 22 grams per kilo body weight (Nyström 1980).
Home range sizes for moose vary with age and male moose in central Sweden
have increasing home range sizes with age, but this does not apply for females. Male
moose (25,9 km2) tend to have larger home ranges than females 13,7 km2) (Cederlund
& Sand 1994). Differences in home range sizes may be more correlated to different
needs for nutrients and for social activity, rather than to just body size (Dussault et
al. 2005). Several studies of moose foraging patterns suggest that moose choose their
diet according to an optimization of net energy intake and not as a response to the
frequency of forage occurrence (Danell & Ericson 1986; Lundberg et al. 1990;
Belovsky 1978). Månsson et al. (2007) on the other hand determined food availability
as the most important variable steering moose intake rate, regardless of spatial scale.
1.4. Hare and moose in mountain birch forest
Food shortage during winters is a limiting factor for several mammalian
herbivores in boreal zones (Skogland 1985; Krebs et al. 1995; Huitu et al. 2003). When
the ground is covered by snow, the accessibility to low plants becomes limited and
for animals that feed above the snow cover, twigs and bark of woody plants is the
7
main available forage (Hodder et al. 2013; Nordengren et al. 2003). When preferred
food items occur at low densities the animal cannot fulfil its food requirements by
selecting the best plants only, but must also eat less preferred plants (Pulliainen &
Tunkkari 1987). Mountain birch is an important food source for several herbivores
in alpine and subalpine areas of Fennoscandia, although not always favoured if
other deciduous species are available in large amounts (Pulliainen & Tunkkari 1987).
In mountain birch forest the low diversity of food plants during winter forces
herbivores above snow cover to keep a narrow diet (i.e., facultative specialization)
(Shipley et al. 2009).
For moose and hare, the quality of woody plants is an important factor determining
foraging patterns (Pehrson 1983b; Ball et al. 2000). These animals are able to
discriminate between and within plants and they feed selectively from plants high
in nutrient content and low in fiber and secondary plant compounds (Rousi et al.
1991; Stolter et al. 2005). Despite the low plant species diversity in mountain birch
forest, herbivores will find variation in forage quantity and digestibility over
multiple scales. Concentrations of nitrogen and secondary compounds in mountain
birch twigs vary within and between individual trees and between sites in the
landscape (Hodar & Palo 1997). Within individual birches, twig diameter, height
level and tissue type are important for physical and chemical characteristics that
determine nutritional quality for mammalian herbivores (Palo et al. 1992; Hodar &
Palo 1997; Nordengren et al. 2003). With increasing diameter the fiber content
increases while the level of plant secondary compounds and nutrients decrease (Palo
et al. 1992; Hodar & Palo 1997).
Herbivory can induce morphological and chemical responses of plants that can
subsequently alter plant selection of herbivores. It has been suggested that such
induced plant responses provide plants with protection from herbivory, as when
insect herbivory on leaves of mountain birch cause subsequent growth of leaves
with reduced nutritional value (Hanhimäki 1989). However, moose winter browsing
and simulated browsing of mountain birch buds prior to leaf development has
induced development of leaves with higher nutritional values (Senn & Haukioja
1994; Stark et al. 2007). Further, clipping of buds yields higher production of new
shoots, as well as leaves with increased sizes (Lehtilä et al. 2000). Danell and HussDanell (1985) showed that hares do not browse differently on slightly or moderately
moose browsed birches, whereas moose preferred previously browsed silver birch
B. pendula and downy birch B. pubescens to unbrowsed birches.
8
1.5. Consequences of contrasting body sizes
Animals require energy for physical functions such as metabolism,
thermoregulation and locomotion. The basal metabolic rate (BMR) is a summary of
the minimum energy expenditure for an endothermic animal at rest (Elgar & Harvey
1987). Among herbivorous mammals, the basic metabolic rate (W/kg/day) decreases
nonlinearly with body weight (Kleiber 1932). Kleiber (1932) suggested that the
metabolic rate scales with body mass to the power of ¾, but this has been the subject
of some debate and other exponents for this relationship have been proposed, the
scaling exponent of ²/3 being one competing hypothesis (Dodds et al. 2001).
Although the energy expenditure of animals is generally dependent on body mass,
other features among the animals such as taxonomic affiliation, habitat, diet and
foraging mode are possible determinants of the FMR (Nagy 2005). A nonlinear
decrease of basal metabolic rate to body weight has implications for the energetic
requirements of animals. Although the total energy requirement is higher for a large
animal, such as the moose, compared to a small animal, such as the mountain hare
(L. timidus), the required amount of food per kg body weight is larger for the hare
than for the moose.
While metabolic rate dictates the energy demand for an animal, the intake of food
is limited by the animal`s gut capacity. There is a linear increase of gut capacity with
body weight resulting in a diminishing metabolic requirement/gut capacity for
larger animals (Demment & Van Soest 1985). This results in the larger animals being
able to tolerate a gut fill of lower quality than smaller ones. In other words, food
quality demands are more relaxed for moose than for hares as moose can make up
for low diet quality by ingesting larger quantities of food. Larger gut size in relation
to body size would allow for a longer retention time of food and hence a more
effective microbial fermentation of food. However, large animals must also
compensate for disadvantages that are related to increased body size. For examples,
the ratio of gut surface: gut volume is negatively correlated with the volume of the
gut, and large animals ingest larger particle sizes, compared to small animals (Clauss
& Hummel 2005). In summary, although mountain hare and moose in mountain
birch forest rely on the same food source whilst enduring severe winter conditions,
they face different digestive and metabolic constraints. These body size
considerations act in concert with the digestive strategy differences described in
section 1.2 to determine the overall nutritional strategy of these contrasting
mammals.
9
1.6. Foraging models/optimality models
In 1966, two simultaneously published studies aimed to explain animal diet
choice through quantification of time or energy expenditures during foraging
(Emlen 1966; MacArthur & Pianka 1966). Both studies suggest that natural selection
should favor an optimized exploitation of available food sources among animals.
Following these publications, a number of studies have explored and suggested
potential mechanisms that might result in an optimized foraging behavior. These
include animal diet choice, patch choice, time allocation choice among patches, and
speed and movement patterns (Reynolds 2012; Wilson et al. 2013; Farnsworth &
Illius 1998; Courant & Fortin 2012). Two basic problems of animal foraging have
been addressed by foraging models, i.e., what food to eat and when to leave each
patch of food. The first problem includes the event of encountering food patches, as
well as the possible capability of the animal to recognize and categorize the food.
The second problem can be measured as the amount of time spent at each patch of
food or as the density of food left in in a patch by a foraging animal (Stephens &
Krebs 1986; Bedoya-Perez et al. 2013).
A model termed the “marginal value theorem” (MVT) predicts that since
environmental characters often differ within the habitat of animals, the optimized
use of the habitat must vary with different patches of the habitat (Charnov 1976;
Parker & Stuart 1976). In order to optimize the habitat exploitation, an animal should
only forage in a patch as long as the rate of energy gain within the patch does not
sink below an average energy gain rate for the whole habitat. A similar way of
reasoning around the optimal utilization of patches is evident in the concept of
“giving up time“(GUT) (Krebs et al. 1974). This is a measurement of a threshold time
each animal reach at a patch while searching for food, before leaving the patch in
search for a new food source. Determining factors for GUT is the quality of each
patch as well as the distance to adjacent patches much in similarity to the MVT
(McNair 1982; Bailey & Provenza 2008). Yet further cost associated with foraging are
to be considered, than those accounted for within the MVT. Costs of risk may be
associated to foraging in a certain patch, and of missed opportunities as other
options for the time spent at the moment of foraging will be lost (Jacob & Brown
2000; Brown 1988). Optimization and MVT seems to work reasonably well for
herbivores when operating at scales where patch depletion occurs but will not
always explain foraging patterns when forage is plentiful (Bailey & Provenza 2008).
However, selection for high plant quality is predicted to increase with high forage
availability, as has been shown for moose (Lundberg & Palo 1993). An optimal
foraging model designed to predict animal distribution between resource patches is
the “ideal free distribution” (IFD) model. This model predicts that the density of
10
animals in a habitat will reflect the density of available resources within the habitat
(Fretwell & Lucas 1970; Stewart & Komers 2012). The idea that herbivores should
strive to optimize their food intake and that the distribution of food resources will
explain the distribution of foraging animals is fundamental for the studies presented
in this thesis. The IFD is tested through hypotheses stated in papers I and II. The
MVT and GUT are focal considerations in the study of patch manipulation presented
in paper III, as well as in paper IV where the focus is on herbivores´ assessment of
costs and benefits associated with different habitats.
Many foraging optimality models assume that animals should be able to estimate
the cost of transit between different patches of feeding areas, as well as the expected
gain of food intake at the different feeding patches. However, the assumption that
animals would have complete knowledge of their surroundings has been questioned
(Carmel & Ben-Haim 2005; Bergman et al. 2005). It has been suggested that animals
have an imperfect knowledge of their surroundings and that they will use recent
experience to evaluate each patch and update their knowledge (Marshall et al. 2013),
or alternatively, use sensory capability such as vision or olfaction (Valone & Brown
1989).
1.7. Scale dependence
Within the field of ecology, the concept of scale became rapidly recognized during
the 1980s (Schneider 2001). In essence, all patterns within an ecological system are
dependent upon the level of scale at which they occur (Wiens 1989). Problems of
scale within the science of ecology are related to both time and space. Some
ecological phenomena that occur over large temporal or spatial scales may be
difficult to monitor or detect while patterns detected at small scales may not
represent patterns occurring at wider scales (Johnson et al. 2001; Schneider 2001;
Månsson et al. 2007). The variability in time and space of ecosystems can be
expressed in numerous fashions such as landscape patchiness, (Wang et al. 2014;
Johnson et al. 2001) species composition (Freestone & Inouye 2006; Mathisen &
Skarpe 2011; Olsson et al. 2012) or process rates (Rastetter et al. 2003; Bardgett &
Wardle 2003; Ohashi & Hoshino 2014). From this follows that all species will be
affected by several different ecological factors simultaneously operating across
multiple scales (Searle et al. 2005; Gross et al. 1995; Owen-Smith 2014). To what
extent different scale-dependent phenomena can affect an animal will depend upon
characters intrinsic to the species (Borthagaray et al. 2012; Eby et al. 2014). Ecological
phenomena operating on small geographical scales are likely to be of importance to
animals that have a restricted mobility, due to size or other physical constraint
11
(Gehring & Swihart 2003). Animals with ability to move over extensive areas are
impacted by and in turn impact ecological phenomena occurring across small as well
as large patches and landscapes (Veen et al. 2012; Edenius et al. 2002; Månsson et al.
2007). As an example, Bergman et al. (2005) showed a difference in feeding strategy
between roe deer (Capreolus capreolus) and rabbits (Oryctolagus cuniculus). An
important result from that study was that rabbits and deer have different
perceptions of available forage, due to their different height. The roe deer make
selection of plants at a patch level as well as choosing plant parts, while rabbits focus
forage selections to a more spatially narrow scale level within plants. Differences in
habitat use over several spatial scales is also expected between hare and moose
(paper II), at least partly due to the perception-based differences presented by
Bergman et al. (2005).
To understand and predict patterns of movement, distribution and resource
utilization of animals it is necessary for researchers to adapt a multi-scale view
(Harvey & Fortin 2013; Van Beest et al. 2011). With increasing scale of observation
the spatial complexity and number of potential interactions between species and
structures grows. Therefore, drivers of foraging decisions by herbivores at small
scales are fairly well understood and predictable, while landscape scale interactions
are more difficult to interpret (Bellu et al. 2012; Van Beest et al. 2011; Månsson et al.
2012). The daily food intake of an animal can be summarized as an aggregate of
many small-scale processes (Laca et al. 2001). Bites are commonly regarded as the
finest unit within the foraging behaviour of animals (Kotliar & Wiens 1990;
WallisDeVries et al. 1999). Short-term intake rates will be influenced by bite size, and
this in turn is decisive for the time it takes to chew each bite. Large bites allows for
the gut to be filled, and for the nutritional requirements to be met more quickly. That
leaves more time for competing activities such as avoiding predators or reproducing
(Shipley 2007). Physical constraints is suggested to be of primary importance for
food intake at small scales such as bites. At the larger scales, such as larger patches
and home ranges, and at larger time scales, spatial memory may be used for foraging
decisions (Bailey et al. 1996). Animals can increase their energy gain by using their
memory of past resource distribution and hence, decrease environmental
uncertainty (Merkle et al. 2014).
Objects that are closely related in space are often more similar than distant objects
and this phenomenon, termed “spatial autocorrelation” is found for most
environmental data (Legendre & Fortin 1989). An example is that food items for
herbivores are likely to be found in patches rather than being evenly distributed in
space due to restricted spread of seeds, or because local conditions for the
establishment and growth of plants vary (Dirnböck & Dullinger 2004). An example
12
of how spatial and temporal autocorrelations operate is how leaf development and
winter dormancy of birch occurs in synchrony within species and at local geographic
sites (Li et al. 2003). This has implications for standard statistical analysis methods
like regressions since assumptions of a random spatial distribution of data becomes
violated (Miller 2012). If the spatial structure of data added into models is not
accounted for, the risk of type I errors increases (Legendre et al. 2002). However,
spatial dependence between observations is not just a nuisance during statistical
analysis; it is one of the most important issues in the analysis of spatial data
(Legendre & Fortin 1989). For an ecologist it is relevant to determine the spatial scale
at which food resources for herbivores are clustered, as it provides an explanation
for the spatial distribution of herbivory (Saracco et al. 2004). To identify the scales of
significant positive (clustered) or negative (regularly spaced) patterns, a statistic
termed local Moran’s I can be used (Anselin 1995), as was used in paper I and II. If
a foraging herbivore closely tracks a certain resource the patterns of spatial
autocorrelation of food intake over increasing spatial scale is assumed to resemble
that of the tracked resource (Saracco et al. 2004). However, a precondition is that the
animal is able to collect information or to respond to environmental variation at the
scales over which the resource is clustered.
1.8. Edge effects
Edges between adjacent patches are central features in landscape ecology as they
control fluxes of energy and material, act as barriers or as specific habitats
(Cadenasso & Pickett 2000; Vidus-Rosin et al. 2012). The abiotic and biotic conditions
along edges will be characterized by conditions prevailing in each of the adjacent
habitats, which makes the perimeter of an ecosystem different from its interior
(Harper et al. 2005; Magura 2002). As an example, forest edges generally exhibit
lighter and dryer conditions than the forest interior (Williams-Linera 1990). Apart
from such abiotic edge effects there are also direct biological effects from the
physiological conditions along edges, such as an increase in light-demanding plant
species near edges due to improved light conditions (Guirado et al. 2006). Indirect
biological effects also depend on the presence of edges, such as rates of predation
and parasitism (Ludwig et al. 2012; Hahn & Hatfield 1995). It was early recognized
that edges would impact the dispersal abilities of game species (Leopold 1987) and
later it has been recognized that species responses to edges can either be positive,
negative or neutral depending on species and context studied (Debinski & Holt
2000). Species that are adapted to conditions intrinsic to interior areas of a certain
habitat will be less abundant near edges and such species are expected to experience
negative effects from habitat fragmentation (Herkert 1994). The importance of
13
negative edge effects to species distributions and abundances have been
investigated in fragmented landscapes such as forests with clear-cuts (Harper et al.
2005; Borchtchevski et al. 2003). The distribution of vegetation and the presence of
forest edges are landscape features that impact the distribution and foraging
activities of herbivores (Ewacha et al. 2014; Brazaitis et al. 2014). Following global
climate change, altered landscape composition is to be expected especially in arctic
and alpine habitats due to ongoing alterations in the location of tree lines (Kullman
& Öberg 2009). To evaluate the consequences of this, it is essential to investigate the
present impact from forest distribution on habitat use of herbivores in arctic and
subarctic environment (paper IV).
1.9. Baiting and supplementary feeding of wild herbivores
As herbivores distribute themselves in response to resource distribution, artificial
placement of food is expected to alter herbivore distribution and forage selection.
This provides the opportunity to steer wildlife away from e.g. areas of heavy road
traffic to decrease the risk of accidents, or from sensitive or economically important
vegetation (Sahlsten et al. 2010; Garrido et al. 2014). Using food to attract animals for
these purposes, or for facilitating research, or tourism that requires observation, or
for trapping, culling or for distribution of vaccines, is referred to as baiting (Dunkley
& Cattet 2003). Supplementary feeding is used for the purpose of increasing or
maintaining population sizes where food availability is a limiting factor, such as
during winter in boreal forests (Putman & Staines 2004). The lack of effect from
artificial feeding on foraging pressure on natural vegetation at the landscape scale
implies that added food mainly impacts feeding patterns at local scales (Van Beest
et al. 2010).
The practice of adding food for wild populations is controversial, as it can
increase the risk of intra- and interspecific disease transmission (Sorensen et al.
2014). Artificial placement of food (which in this thesis refers to food addition for
the purposes of baiting or supplementary feeding) can also impact non-target
species (Pedersen et al. 2014). Placement of food can also cause problems such as
encounters between animals and people, and nuisance behavior among animals that
are drawn to human facilities. Steyaert et al. (2014) suggested that individual
variation in responses to additional food will dilute the population responses to
added food. Studies of mountain hares have revealed that individuals will be more
or less prone to use supplementary food or bait depending on their condition and
that only a subset of a target population would use it (Newey et al. 2010; Bisi et al.
2011). The response of herbivores, like moose, to additional food also depends on
14
the composition of the surrounding landscape and on the prior distribution of the
target population (Gundersen et al. 2004). In subarctic birch forest, the low diversity
of food plants that are available above the snow cover during winter limits herbivore
food choices. The daily food intake and hence the daily selection of foraging sites is
imperative for hares to maintain their energy balance during winter in northern
environments (Thomas 1987). Mountain hares in subarctic birch forest therefore
provide a suitable system for studies of herbivore responses to food patch
manipulation, (paper III in this thesis).
2. OBJECTIVES
As summarized in the review above, mountain hare and moose ought to respond to
variation in plant quality and quantity. It is expected that their winter browsing will
be located in areas that contain high availability of good-quality forage relative to
the average availability in the surrounding landscape. As the distribution of good
patches for foraging is steered by e.g., topography, elevation and soil nutrients,
herbivores would show predictable foraging patterns over time and over the
landscape. Given the physiological constraints of these species, hare and moose are
expected to respond to resource allocation at contrasting spatial scales, which in turn
would lead to separate location of their foraging activity. As herbivores
continuously track good areas to feed in, manipulation of forage distribution should
result in altered foraging distribution. Forests provides shelter form severe weather
and high availability of winter browse relative to un-forested areas. Food resources
situated in forest should therefore be preferred by herbivores over resources situated
in un-forested areas. These predictions were tested in the four studies that are
presented in this thesis.
In paper I, it was tested if browsing patterns by moose in a mountain birch forest
were consistent and, hence, predictable between two periods separated by 14 years.
It was ascertained whether density of food plants could explain the distribution of
moose browsing and if the spatial scale where moose browsing was clustered was
similar between the two periods.
Paper II investigated whether the foraging distribution of hare and moose would
be separated spatially as predicted by their contrasting body size, even in a situation
when the two species share the same principal food source. This was tested on
several spatial scales, from the level of individual plants to the landscape scale. It
was predicted that hares would target areas with high densities of small birches
while moose would prefer areas with larger trees.
15
The aim of paper III was to test if the addition of fodder to local patches would
enhance patch quality perceived by hares, so that the utilization of natural food
would increase. It was assessed how the quality and quantity of the added food
would steer the local use of vegetation. It was predicted that browsing on birch
induced by the addition of food would increase with increasing birch density and
with previous patch utilization.
In paper IV, it was investigated whether mountain birch forest cover would impact
habitat use of mountain hares. It was tested if the intake of added food would
depend on distance from forest edges, and if microclimate characters and the
presence of red fox would differ between forested and treeless areas.
3. METHODS
3.1.
Study area
The field studies were conducted in a subarctic tundra landscape near the village
of Abisko (68°21N, 18°49 E) (Figure 3 a-b). The forest in this area is part of the
northern boundary of tree growth in Scandinavia and is exposed to severe weather
conditions at all times of the year. The latitude, along with a mountainous
topography and the close proximity to the Atlantic coast, characterizes the climate
and weather (Holmgren & Tjus 1996). The Abisko Valley has lower amounts of
precipitation compared to the surrounding mountain region, with a yearly
precipitation of 300 mm per year. The snow cover amounts on average to 50 cm at
its peak in March (Kohler et al. 2006).
The mountain birch forest landscape is characterized by a patchy tree growth
intersected by open heathland (Figure 4). Mountain birches are generally 4-6 meters
high and commonly polycormic (multi-stemmed) on dry and nutrient-poor sites
while monocormic trees (single-stemmed) grow on more moist and rich sites
(Bylund & Nordell 2001). The most common ground-layer vegetation consists of
dwarf shrubs such as bilberry (Vaccinium myrtillus), crowberry (Empetrum nigrum)
and dwarf-birch (B. nana), along with some species of grass, mosses and lichens
(Tømmervik et al. 2009). In addition to mountain birch, tree species present in the
area are willows, grey alder (Alnus incana), pine (Pinus sylvestris) and aspen (Populus
tremula) (Berglund et al. 1996).
16
Torneträsk
Abisko
a.
b.
Figure 3 a-b. Location (a) of the study area in northwest Sweden, marked with a black
square. Orthophoto (b) of the northern part of the Abisko Valley with Mt. Njulla
seen in the upper left corner of the image. The Abisko Scientific Research
Station is marked with a white arrow.
Figure 4.
Part of the study area viewed from Mt. Njulla with the lake Torneträsk seen on
the left in the image and the tree line on the far right. The mires, heaths and
17
lakes that intersect the forest are seen as white patches. Photo by Sara
Öhmark.
The cover of shrub and trees has increased in the Abisko Valley from the 1970s
to 2010 (Rundqvist et al. 2011). This vegetation increase is mostly observed for
mountain birch and dwarf birch, while willows show inconsistent patterns of
growth with time. The vegetation change is possibly due to past and present human
activities in the area, due to recovery from insect outbreaks and/or due to an ongoing
climate warming (Emanuelsson 1987; Tenow 1996; Callaghan et al. 2010; Kullman &
Öberg 2015). The mountain birch forest is unmanaged but it is affected by defoliation
during repetitive events of large-scale insect outbreaks (Tenow 1996). An outbreak
of the autumnal moth (Epirrita autumnata) defoliated and to large parts killed the
birch forest in the Abisko Valley in 1955/56. Much of the present forest is therefore
derived from basal sprouts from stems killed by the moth larvae (Tenow 1996).
Another factor behind killings and damage of tree stands in the area is the
occurrence of severe frost during growing seasons and during dormant stages of the
trees. Mountain birch grows near its altitudinal limit in the Abisko Valley and is
affected by aboveground and belowground temperature. Growth rate and nitrogen
uptake are both limited by low temperatures (Weih & Karlsson 2002). The woody
vegetation in the area is also subjected to herbivory during winter and summer by
vertebrate herbivores; these are apart from moose and hare ptarmigan (Lagopus
mutus), willow grouse (L. lagopus) and several species of voles (Microtinae). Moose
browsing has a notable impact on the vegetation in the area. Young pines (Pinus
silvestris) in the Abisko Valley show signs of continuous browsing by moose and this
herbivory in combination with fungal infection is suggested to be a primary cause
of suppressed pine recruitment in the area (Stöcklin & Körner 1999). The Abisko
Valley is used for reindeer grazing during summer and autumn (information from
the Sametinget webpage: www.sametinget.se/9392).
Research on climate, geology and ecology in the Abisko Valley and the
surrounding area is intense since the establishment of the Abisko Scientific Research
Station in 1913. Environmental conditions such as snow depth and daily
temperatures and wind speeds are monitored, and some of these recordings have
been ongoing for over a century (Jonasson et al. 2012). The Abisko national park
covering a 77 km2 area was formed in 1909. Within the protected area lies the Abisko
tourist station built in 1902, a ski lift, and the northern end of the Kungsleden trail,
a path that apart from serving as a ski trail during winter is used by snow mobiles
and dog sleds. During summer, the path is mainly utilized by hikers. At present the
18
Abisko national park is the most visited national park in the Norrbotten county with
some 40 000 visitors per year.
3.2. Data collection
For paper I and II we made observations of un-manipulated winter browsing by
hare and moose on mountain birch and willows. It is possible to distinguish hare
browsing from moose browsing by the appearance of the browsed twig. Hares clip
twigs with their sharp incisors, leaving a smooth cut surface (Figure 5 a). Moose use
their molars to rip off twigs and this gives a rugged surface at the cut (Figure 5 b).
Further, the age of the cut is revealed by the color of the twig at the cut, as the wood
turns grey with time. Twigs cut during the current winter season has a light color
that is easily distinguishable from twigs cut during previous winter seasons (Figure
5 a-b).
a.
b.
Figure 5 a-b. Birch twig cut by winter browsing hare (a) and moose (b). The twig cut by hare
was browsed prior to the winter season when the photo was taken, which is
apparent from the dark color of the wood at the cut, while the moose browsing
was recent, as is apparent from the light color of the wood at the cut. Photos by
Sara Öhmark.
Occasionally it was difficult to discern if browsing on very fine birch and willow
twigs was done by hare or willow grouse. If there was any doubt, the browse was
noted as caused by an unknown browser. Although heavy reindeer summer
browsing can reduce shoot length of willows, this occurs through growth responses
19
following leaf-stripping, not through clipping of twigs, and therefore this is highly
unlikely to be confounded with the effects of moose browsing (Olofsson &
Strengbom 2000). Lichens are the principal winter food for reindeer in Fennoscandia,
while utilization of vascular plants increase with high reindeer population density
and low availability of lichens (Danell et al. 1994; Heggberget et al. 2002; Kumpula
2001; Skogland 1984).
During the data collection in 2010, there was no reindeer tracks within the sample
plots. Reindeer tracks were observed on a few occasions in 2010 in the study area,
but no browsing on birch or willow twigs was found near reindeer tracks. It is
therefore unlikely that effects of reindeer winter browsing would compromise the
results of the browsing survey of moose presented in papers I and II. Moose tracks
were commonly found below birches and willows with fresh browsing.
3.3. Response variables
In the studies presented in this thesis, foraging activity of free-ranging mountain
hare and moose on winter browse was measured and set in relation to natural
environmental conditions such as vegetation density, snow depth and elevation.
Foraging intensity by hares on added food under varied natural conditions was
measured. Finally, foraging intensity by hares on natural browse in response to
addition of forage was assessed. For papers I, II and III, the relative browsing
intensity between different sites in the study area was measured, but not the
absolute intake by hare or by moose. For the purpose of studying relative offtake of
browse per site, it was sufficient to count the number of apical birch and willow
twigs cut by moose or by hare per unit area.
For paper I, the accumulated moose browsing on birch and willow deriving from
the winter seasons of 1998-1996 and 2009-2010 was measured. Thus, only
observations of fresh moose browsing were used. The distance between sites with
different browsing intensities was measured to assess the occurrence of spatial
autocorrelation (clumped distribution) of foraging activity at different spatial scales.
The relative moose density for the two winter seasons was estimated by counting
numbers of moose tracks crossing transects.
For paper II, hare and moose browsing deriving from both the winter season of
2009-2010 and from previous winters was measured (Figures 4a-b). It was noted if
both fresh/old browsing and hare/moose browsing occurred within the same sample
sites and at the same birch or willow stems. Distance between sample plots to test
20
for the occurrence of spatial autocorrelation at different spatial scales was assessed
also in this study.
For paper III, numbers of hare-browsed birch twigs were measured at sites
manipulated through addition of food and these observations were compared to
numbers of browsed twigs at un-manipulated sites. Numbers of visits by hares after
the termination of the experiment at ex-manipulated sites and at control sites were
measured as the number of hare tracks crossing these sites. Daily observations of
browsing activity was measured at some manipulated sites both while added food
was available for hares and after the food had been depleted by hares.
For paper IV, hare responses to forest cover was measured as the amount of
consumed added forage in areas with and without mountain birch forest. In this
study, the effect of forest cover on microclimate (local air temperature and wind
speed) was also measured.
3.4. Design of sample plots
For paper III and IV, the field studies included artificial placement of food for
hares. This was either hay or straw, tied in 30-gram bunches that were tied to trees
or shrubs, or alternatively, where no vegetation was present, to sticks that were
inserted into the snow or into lake ice using a drill. Visual cues of hare activity was
also used (fresh browsing on twigs, tracks, urine or faeces) to determine if visits from
hares had occurred at the artificially placed food (Figure 6). Such cues were often
quite evident but after heavy snowfall or during windy conditions, tracks and faeces
would be concealed. Surveillance of the sites with added food using film cameras
provided a complement to the visual cues of hare visits, and also revealed if other
species than hares had visited the sites and/or utilized the added food. The film
material also revealed the diurnal activity patterns of hares in the study area.
21
Figure 6.
Hare tracks and faeces at a site with added food; bunches of hay attached to a
mountain birch.
We measured vegetation density and hare browsing intensity within sample
plots in all four studies presented in this thesis, but the size and shape of the plots
differed between studies. Plots used for paper III (5*5 m with addition of two
transects placed adjacent to each plot of 2*20 m=105 m2) was smaller compared to
the plots presented in papers I and II (25*25 m=625 m2). The design of sample plots
was intended to represent local vegetation characteristics and browsing patterns.
Where mountain birches were polycormic (as seen in Figure 6), an individual birch
could cover several square meters. The sample plots used in papers I and II were of
sufficient size to include several polycormic birches. They would generally also
include both willow and birch vegetation where willow shrubs of large sizes
occurred, which provided information of browsing pressure on birch adjacent to
willows. The inventory of these plots was more time consuming compared with the
plots used for paper III. The large number of sample plots necessary to provide
replication of all combinations of treatments in addition to controls called for a
design that allowed for a rapid inventory of vegetation and hare browsing. The
22
transects in paper III provided measurements of variation in vegetation and
browsing pressure while reducing the surface assessed, and hence the time spent
per site. Another reason for restricting the size of the sample plots for paper III was
that we aimed at comparing responses from hares to different site treatments in
nearby and, hence, according to the principle of spatial autocorrelation, similar sites.
The size of the sample plots partially determined the size of the blocks that contained
groups of plots. The chance of observing browsing within a plot will increase with
the size of the sample plot, but browsing intensity measured as cut twigs per unit
area or percentage of trees with browsing is not impacted by this.
4. RESULTS AND DISCUSSION
4.1. Paper I
The measurements of vegetation density in 1996 and in 2010 follows the general
trend with increasing cover and density of trees and shrubs described by Olofsson
et al. (2009) and Rundqvist et al. (2011). Both the number of sample plots with
occurrence of willows and the mean density of willows per plot increased from 19962010, but Rundqvist et al. (2011) did not find a consistent trend in the cover of
willows in the Abisko Valley from 1976-1977 to 2009-2010. Results from paper I
shows that birch densities in 1996 were positively correlated to birch densities in
2010 but for willows there was no such consistency over time.
Microsite conditions exhibit sharp contrast over short distances in tree line
ecotones in Fennoscandia due to the varied local topography and this gives a
consistent spatial pattern of growth, morphology and reproduction patterns of
mountain birch (Anschlag et al. 2008). Mountain birch reproduces with root suckers
as well as sexually. After major disturbances like insect attacks, the regrowth of root
shoots is therefore a major part of the recovery of the birch forest (Tenow & Bylund
2000). Root shoots are less sensitive to herbivory than the growth of seedlings, which
adds to the importance of asexual regrowth after disturbances and this promotes
consistent spatial distribution of mountain birch over time (Lehtonen & Heikkinen
1995). In paper I it was predicted that moose foraging patterns in mountain birch
forest should be consistent over time and results showed that the spatial scale where
foraging decisions takes place remained the same after 14 years. Further, moose
browsing was concentrated to the same sites in 2010 that were most intensely
browsed in 1996.
23
These findings demonstrate that moose browsing patterns can be predicted over
time. Defining factors and processes that remains stable over time are important for
the success of management and conservation actions as these rely on accurate
predictions of future conditions (Sutherland 2006; Seiler 2005; Gordon et al. 2004).
There was less snow in 1996 than in 2010. If snow depth is positively related to
vegetation density, deep snow could hinder moose from utilizing sites with good
availability of forage. However, snow depth was not a significant parameter in a
model predicting moose browsing intensity. There was no positive correlation
between birch density and snow depth and a plausible explanation for this is that
local topography is a strong determinant of snow accumulation (Grünewald et al.
2013). The total density of willow and birch was not a determinant of browsing on
birch at multiple spatial scales. However, both willow and birch densities clustered
at the same spatial scale as moose browsing showing that vegetation is a
determinant for moose foraging at certain spatial scales.
There was no significant effect from snow depth on moose foraging distribution.
Moose are well adapted to cope with high snow depth compared to other ungulates
(Telfer & Kelsall 1984). Even if the local variation in snow depth may hinder moose
from accessing forage at certain sites, it would not explain foraging patterns of
moose in the study area.
4.2. Paper II
Hare and moose targeted different areas during foraging and moose utilized
higher and thicker birches than the hares did. Hares are able to walk on the surface
of the snow while moose sinks through the snow, which will allow the hare to reach
high-growing browse at sites with high snow accumulation. However, the mean
snow depth of 50 cm at the peak in March would not be enough for the hares to
reach to the same heights as moose and this restricts the possibility for hare to
respond to the variation with height in forage quality and quantity that birches
display (Nordengren et al. 2003). There was a positive correlation between finestemmed and thick-stemmed birches, which is expected from the occurrence of root
suckers and basal sprouts. Hares tracked areas with high densities of birches
regardless of stem diameters. Moose foraging distribution was positively correlated
to birch density only when birches of >3 cm basal diameter was considered. This can
explain the results in paper I, which shows that the density of birches of any
diameter was not an explanatory factor for moose foraging distribution. As small
and large birches would cluster in the same areas, the selection for different tree sizes
24
would not alone explain a spatial separation of feeding sites. Hares showed a
clumped distribution of their foraging at smaller spatial scales (<500 m) than moose
(1500 m). A greater selectivity of hares at small scales compared to moose is to be
expected from their body size, and this has also been demonstrated, e.g., for cattle
(Bos Taurus) and brown hares (L. europaeus) and for rabbits and roe deer (Bergman
et al. 2005; Veen et al. 2012).
Moose browsing on birch occurred in more sites and was more intense than hare
browsing but the total browsing pressure was low on birch. Neither moose nor hares
would therefore experience a depletion of birch browse in the study area and
intraspecific competition for birch would not explain the separated browsing
patterns. The browsing pressure from moose on willows was high wherever willow
occurred, while only a few observations of hare browsing on willow was made. It is
therefore likely that hares are prevented from utilizing willows due to intense moose
browsing. Patterns of spatial autocorrelation of moose browsing on birch was
positively correlated to that of willow. Both hare and moose preferably browsed the
same sites from year to year, as was evident from the positive correlation between
old and new browsing. This makes the foraging patterns of hare and moose
predictable and this behavior has been demonstrated previously albeit at larger
(home-range) spatial scales (Dahl & Willebrand 2005; Sweanor & Sandegren 1989).
4.3. Paper III
Results from this paper demonstrated that it is possible to manipulate overall
patch quality perceived by hares by adding food. The added food that was least
consumed by hares was oat straw and this food could not increase browsing
pressure on nearby birch to the same extent as the more preferred foods: hay and
hay treated with NaCl. The amount of added food also influenced the browsing
pressure on nearby birches so that birch browsing was greatest where the highest
amount of food was added. Our results underline the importance of forage
distribution for hare foraging patterns and they conform to the prediction of the
marginal value theorem that utilization of a patch should increase with patch quality
(Charnov 1976). Natural patch characteristics influenced the response to patch
manipulation so that more birch was browsed where vegetation was dense and
where previous browsing pressure was high. The annual browsing pressure was
low (26% of plots were browsed) but browsing derived from previous winter
seasons showed that over a period of several years a majority of the sampled sites
were used. A few sites had only fresh browsing, showing that hares would browse
also in sites that had not been used during previous years. This may seem
25
contradictory to previously demonstrated site-fidelity among hares, including our
own results in paper II (Öhmark et al. 2015; Dahl & Willebrand 2005). One plausible
explanation is that habitat use by hares depends on population density and hares
will utilize a greater portion of their environment during population highs
(Pulliainen & Tunkkari 1987).
The frequency of visiting hares at plots with previous addition of food remained
higher than in control plots after three weeks but the browsing intensity decreased
immediately after depletion of the added food. This indicates that mountain hares
remembers spatial distribution of resources. After one year after the experiment,
there was no increased browsing pressure in ex-feeding sites. Damage to mountain
birch can alter chemical composition and growth during subsequent growth seasons
and this can in turn increase herbivory of invertebrate herbivores on winter-browsed
trees (Lehtilä et al. 2000; Danell et al. 1997). However, our results are in line with a
previous study where hares showed indifferent response to simulated moose winter
browsing on birch (Danell & Huss-Danell 1985).
4.4. Paper IV
Forest cover was not a determinant of utilization of the added food for hares in
the mixed landscape of mountain birch forest and subarctic mires and heaths. This
demonstrates a plasticity in hare foraging behavior that enables them to use
resources across varying environments. Camera trapping showed the strict
nocturnal activity pattern that has been previously described for mountain hares
(Rehnus 2014).
Earlier studies have either found preference for forested habitat over open areas
(Pulliainen & Tunkkari 1987) or indifferent response to forested vs. open areas (Dahl
2005). The lake ice was an un-preferred habitat and an edge effect was evident as
utilization of added food decreased gradually from the interior of forest onto the
lake ice. While the lake ice offered no natural shelter or food, low shrubs were
available for the hares at the mires and heaths as the snow cover was thinner in these
areas than in adjacent forest. Mountain birch forest was warmer than adjacent open
habitats, but only when average temperatures dropped below -15°C. It is unclear if
this difference in temperature is of ecological importance for the hares. Behavioral
adaptation to wind (orientation, posture, shelter seeking) has been observed for
mountain hares (Thirgood & Hewson 1987; Flux 1970) while observations of a Finish
hare population showed little or no effect from temperatures down to -30 on habitat
selection (Pulliainen 1982). Wind speed was lower in forested than in open areas.
26
During recent decades an increase in the cover and density of trees and shrubs has
been observed in arctic areas (Rundqvist et al. 2011; Kullman & Öberg 2015). This
will provide more food for hares both in areas with forest cover and where low
shrubs constitute the only vegetation, and it will also provide more shelter from
wind and warmer microclimatic conditions.
5. CONCLUSIONS
Arctic areas are undergoing an increase in vegetation density and will be
affected by future climate warming. Herbivores influence vegetation dynamics in
subarctic areas and these influences interact with effects from global climate change
on vegetation distribution and density. In this perspective, key factors that are
important for subarctic herbivores need to be determined. This thesis sheds some
light on factors related to scale and forage distribution for two high profile, high
impact herbivores in the subarctic. The species show high fidelity to foraging sites
over time and seek habitats with high density of forage. This predictability of
feeding patterns is of essence for conservation and management practices as the
chance of reaching intended goals will increase when accurate predictions of future
conditions are made.
Forage density will only be a determinant of feeding patterns of hare and moose
at certain spatial scales, and this underlines the importance of taking spatial scales
and landscape context into consideration during ecological studies and in
conservation and management planning. Different species will respond to resource
heterogeneity at different spatial scales, and one reason is that body size restricts the
ability to perceive and respond to resource heterogeneity at different scales. By
adding forage, it is possible to increase local habitat quality and, thereby, making an
area more attractive for hares but this effect is not sustained after the added food is
removed. Apparently, hares are sensitive to changes in its environment and are able
to track changes in habitat quality over time.
The response of hares to mountain birch forest cover was inconsistent: hares
avoided lake ice and preferred nearby forest, while there was either an indifferent
or a positive response to subarctic mires and heaths compared to nearby forest. This
shows that hares will avoid extreme environments like lake ice, but they can assess
forage availability on subarctic mires and heaths as well as in mountain birch forest.
Wind speeds were lower, and temperatures higher near ground in mountain birch
forest than on nearby open areas. With increasing cover of forest and shrubs in
27
subarctic and arctic areas, the access to forage will increase for both hare and moose
and they will find forage at higher elevations. This will also provide more sheltered
habitat during winter, which may be especially important in subarctic areas where
winter conditions are severe.
6. ACKNOWLEDGEMENTS
I would like to thank my supervisors Thomas, Glenn and Bege for all the support
you gave throughout my time as a PhD student. Thank you for believing in me and
for lending me your experience and your patience! I would also like to thank Göran
Ericsson and Kerstin Sunnerheim who were my mentors and Clare McArthur for
showing me the benefits of camera traps and for giving comments to several
manuscripts. Thank you, Julia Hjalmarsson, for your comments to the thesis. I thank
the staff at the Abisko Scientific Research Station for all the practical help you gave
during field work and for making me feel welcome during every visit in Abisko.
Jennie, Johan, Sofia, Alireza, Zimon, Jossan and Julia, thank you for enduring those
subarctic storms (real ones as well as perceived) during field work, and thank you
for all your help and for the good company!
Jennie, Jenny Z, Joel, Mattias, Anna-Maria, Freddan, Julia, Saba, Rizan, Hugo,
Ghadir, Nazlin, Majid, Erika W, Anna P, Torborg, Håkan N, Lisbeth, Viktoria,
Veronica, Ingrid, Stefan B, Peter G, Svante, Nils, Annelie, Thomas N, Natalia, Amelie
and all the other great people that have been in the O- and the S-building during the
past years; how happy I am to have met you! With you I have found close friendship,
great roommates, and good company for both happy and sincere discussions during
lunches and fikas, moral support and good advice in times of need. I will miss you!
Let’s meet for a fika a.s.a.p!
Mamma och PeO, pappa och Eivor, kära syster Lina med familj, tack för att ni
alltid finns här och för att ni stöttar mig, det betyder allt för mig. Tjejkompisarna Ida,
Maria, Viktoria, Frida, Erika och Katarina, fastän vi ses alltför sällan så känns ni nära!
Fredrik, Astrid och lillskrutten i magen, ni är världens finaste familj och jag är så
glad över att få dela tillvaron med er. Tack Fredrik, för ditt stöd och ditt tålamod
som gjorde slutförandet av avhandlingen möjlig för mig.
28
29
7. REFERENCES
Angerbjörn, A. & Pehrson, Å., 1987. Factors influencing winter food choice
by mountain hares (Lepus timidus L.) on Swedish coastal islands.
Canadian Journal of Zoology, 65, pp.2163–2167.
Anschlag, K., Broll, G. & Holtmeier, F.-K., 2008. Mountain Birch
Seedlings in the Treeline Ecotone, Subarctic Finland: Variation in
Above- and Below-Ground Growth Depending on Microtopography.
Arctic, Antarctic, and Alpine Research, 40(4), pp.609–616.
Anselin, L., 1995. Local indicators of spatial association-LISA.
Geographical Analysis, 27, pp.93–115.
Atsatt, P.R. & O’Dowd, D.J., 1976. Plant defense guilds. Science (New
York, N.Y.), 193(4247), pp.24–29.
Bailey, D.W. et al., 1996. Mechanisms that result in large herbivore grazing
distribution patterns. Journal Of Range Management, 49, pp.386–400.
Bailey, D.W. & Provenza, F.D., 2008. Mechanisms determining largeherbivore distribution. In Resource Ecology Spatial and Temporal
Dynamics of Foraging. pp. 7–28.
Ball, J.P., Danell, K. & Sunesson, P., 2000. Response of a herbivore
community to increased food quality and quantity: an experiment with
nitrogen fertilizer in a boreal forest. Journal of Applied Ecology, 37,
pp.247–255.
Ballaré, C.L., 2014. Light regulation of plant defense. Annual review of
plant biology, 65, pp.335–63.
Bardgett, R.D. & Wardle, D.A., 2003. Herbivore-mediated linkages
between aboveground and belowground communities. Ecology, 84(9),
pp.2258–2268.
Bedoya-Perez, M.A. et al., 2013. A practical guide to avoid giving up on
giving-up densities. Behavioral Ecology and Sociobiology, 67(10),
pp.1541–1553.
30
Van Beest, F.M. et al., 2010. Long-term browsing impact around
diversionary feeding stations for moose in Southern Norway. Forest
Ecology and Management, 259, pp.1900–1911.
Van Beest, F.M. et al., 2011. What determines variation in home range size
across spatiotemporal scales in a large browsing herbivore? Journal of
Animal Ecology, 80, pp.771–785.
Bellu, A. et al., 2012. Habitat use at fine spatial scale: How does patch
clustering criteria explain the use of meadows by red deer? European
Journal of Wildlife Research, 58, pp.645–654.
Belovsky, G.E., 1978. Diet optimization in a generalist herbivore: the
moose. Theoretical population biology, 14(1), pp.105–134.
Belovsky, G.E. & Schmitz, O.J., 1994. Plant defenses and optimal foraging
by mammalian herbivores. Journal of Mammalogy, 75, pp.816–832.
Berglund, B.E. et al., 1996. Holocene forest dynamics and climate changes
in the Abisko area, northern Sweden - the Sonesson model of
vegetation history reconsidered and confirmed. Ecological Bulletin, 45,
pp.15–30.
Bergman, M., Iason, G.R. & Hester, A.J., 2005. Feeding patterns by roe
deer and rabbits on pine, willow and birch in relation to spatial
arrangement. Oikos, 109(3), pp.513–520.
Bisi, F. et al., 2011. The strong and the hungry: bias in capture methods for
mountain hares Lepus timidus. Wildlife Biology, 17(3), pp.311–316.
Björnhag, G. & Snipes, R.L., 1999. Colonic separation mechanism in
lagomorph and rodent species - a comparison. Zoosystematics and
Evolution, 75(2), pp.275–281.
Borchtchevski, V.G. et al., 2003. Does fragmentation by logging reduce
grouse reproductive success in boreal forests? Wildlife Biology, 9,
pp.275–282.
Borthagaray, A.I., Arim, M. & Marquet, P.A., 2012. Connecting landscape
structure and patterns in body size distributions. Oikos, 121(5), pp.697–
710.
31
Brazaitis, G. et al., 2014. Landscape effect for the Cervidaes Cervidae in
human-dominated fragmented forests. European Journal of Forest
Research, 133, pp.857–869.
Brown, J.S., 1988. Patch use as an indicator of habitat preference, predation
risk, and competition. Behavioral Ecology and Sociobiology, 22,
pp.37–47.
Bylund, H. & Nordell, K.O., 2001. Biomass proportion, production and leaf
nitrogen distribution in a polycormic mountain birch stand (Betula
pubescens ssp. czerepanovii) in northern Sweden. In F. E. Wielgolaski,
ed. Nordic mountain birch ecosystems. Parthenon Publishing Group
Inc., New York, pp. 115–126.
Cadenasso, M.L. & Pickett, S.T.A., 2000. Linking forest edge structure to
edge function: mediation of herbivore damage. Journal of Ecology,
88(1), pp.31–44.
Callaghan, T. V et al., 2010. A new climate era in the sub-Arctic:
accelerating climate changes and multiple impacts. Geophysical
Research Letters, 37, pp.1–6.
Carmel, Y. & Ben-Haim, Y., 2005. Info-gap robust-satisficing model of
foraging behavior: do foragers optimize or satisfice? The American
naturalist, 166(5), pp.633–641.
Cederlund, G. & Sand, H., 1994. Home-Range Size in Relation to Age and
Sex in Moose. Journal of Mammalogy, 75, pp.1005–1012.
Cederlund, G.N. et al., 1986. Seasonal variation in mandible marrow fat in
moose. Journal of Wildlife Management, 50(4), pp.719–726.
Cederlund, G.N., Sand, H.K.G. & Pehrson, Å., 1991. Body mass dynamics
of moose calves in relation to winter severity. Journal of Wildlife
Management, 55(4), pp.675–681.
Charnov, E.L., 1976. Optimal foraging, the marginal value theorem.
Theoretical Population Biology, 9(2), pp.129–136.
Clauss, M. et al., 2007. A case of non-scaling in mammalian physiology?
Body size, digestive capacity, food intake, and ingesta passage in
32
mammalian herbivores. Comparative Biochemistry and Physiology - A
Molecular and Integrative Physiology, 148(2), pp.249–265.
Clauss, M. & Hummel, J., 2005. The digestive performance of mammalian
herbivores: why big may not be that much better. Mammal Review,
35(2), pp.174–187.
Condon, B. & Adamowicz, W., 1995. The economic value of moose
hunting in Newfoundland. Canadian Journal of Forest Research,
25(2), pp.319–328.
Courant, S. & Fortin, D., 2012. Time allocation of bison in meadow patches
driven by potential energy gains and group size dynamics. Oikos,
121(7), pp.1163–1173.
Dahl, F., 2005. Distinct seasonal habitat selection by annually sedentary
mountain hares (Lepus timidus) in the boreal forest of Sweden.
European Journal of Wildlife Research, 51, pp.163–169.
Dahl, F. & Willebrand, T., 2005. Natal dispersal, adult home ranges and site
fidelity of mountain hares Lepus timidus in the boreal forest of
Sweden. Wildlife Biology, 11, pp.309–317.
Danell, K. et al., 1994. Food plant selection by reindeer during winter in
relation to plant quality. Ecography, 17, pp.153–158.
Danell, K. & Ericson, L., 1986. Foraging by moose on two species of birch
when these occur in different proportions. Holarctic Ecology, 9, pp.79–
83.
Danell, K., Haukioja, E. & Huss-Danell, K., 1997. Morphological and
chemical responses of mountain birch leaves and shoots to winter
browsing along a gradient of plant productivity. Ecoscience, pp.296–
303.
Danell, K. & Huss-Danell, K., 1985. Feeding by insects and hares on
birches earlier affected by moose browsing. Oikos, 44, pp.75–81.
Dearing, M.D., Foley, W.J. & McLean, S., 2005. The influence of plant
secondary metabolites in the nutritional ecology of herbivorous
33
terrestrial vertebrates. Annual Review of Ecology, Evolution, and
Systematics, 36(1), pp.169–189.
Dearing, M.D., Mangione, A.M. & Karasov, W.H., 2000. Diet breadth of
mammalian herbivores: nutrient versus detoxification constraints.
Oecologia, 123(3), pp.397–405.
Debinski, D.M. & Holt, R.D., 2000. A survey and overview of habitat
fragmentation experiments. Conservation Biology, 14(2), pp.342–355.
Demment, M.W. & Greenwood, G.B., 1988. Forage ingestion: effects of
sward characteristics and body size. Journal of animal science, 66(9),
pp.2380–2392.
Demment, M.W. & Van Soest, P.J., 1985. A nutritional explanation for
body-size patterns of ruminant and nonruminant herbivores. The
American Naturalist, 125, p.641.
Dirnböck, T. & Dullinger, S., 2004. Habitat distribution models, spatial
autocorrelation, functional traits and dispersal capacity of alpine plant
species. Journal of Vegetation Science, 15, pp.77–84.
Dodds, P.S., Rothman, D.H. & Weitz, J.S., 2001. Re-examination of the 3/4
law of metabolism. Journal of Theoretical Biology, 209(1), pp.9–27.
Dunkley, L. & Cattet, M.R.L., 2003. A comprehensive review of the
ecological and human social effects of artificial feeding and baiting of
wildlife. Canadian Cooperative Wildlife Health Centre: Newsletters &
Publications, p.21.
Dussault, C. et al., 2005. Space use of moose in relation to food availability.
Canadian Journal of Zoology, 83(11), pp.1431–1437.
Eby, S.L. et al., 2014. The effect of fire on habitat selection of mammalian
herbivores: the role of body size and vegetation characteristics. The
Journal of animal ecology, 83(5), pp.1196–1205.
Edenius, L. et al., 2002. The role of moose as a disturbance factor in
managed boreal forests. Silva Fennica, 36, pp.57–67.
34
Elgar, M.A. & Harvey, P.H., 1987. Basal Metabolic Rates in Mammals:
Allometry, Phylogeny and Ecology. Functional Ecology, 1(1), pp.25–
36.
Emanuelsson, U., 1987. Human influence on vegetation in the Torneträsk
area during the last three centuries. Ecological Bulletins, 38, pp.95–
111.
Emlen, J.M., 1966. The role of time and energy in food preference. The
American Naturalist, 100, pp.611 – 617.
Ewacha, M.V.A., Roth, J.D. & Brook, R.K., 2014. Vegetation structure and
composition determine snowshoe hare (Lepus americanus) activity at
arctic tree line. Canadian Journal of Zoology, 92, pp.789–794.
Farnsworth, K.D. & Illius, A.W., 1998. Optimal diet choice for large
herbivores: An extended contingency model. Functional Ecology,
12(1), pp.74–81.
Flint, H.J. & Bayer, E.A., 2008. Plant cell wall breakdown by anaerobic
microorganisms from the mammalian digestive tract. Annals of the
New York Academy of Sciences, 1125, pp.280–288.
Flux, J.E.C., 1970. Life history of the mountain hare (Lepus timidus
scoticus) in north-east Scotland. Journal of Zoology, 161(1), pp.75–
123.
Fraenkel, G.S., 1959. The raison d ’ etre of secondary plant substances.
Science, 129, pp.1466–1470.
Freeland, W.J. & Janzen, D.H., 1974. Strategies in herbivory by mammals:
the role of plant secondary compounds. The American Naturalist,
108(961), pp.269–289.
Freestone, A.L. & Inouye, B.D., 2006. Dispersal limitation and
environmental heterogeneity shape scale-dependent diversity patterns
in plant communities. Ecology, 87(10), pp.2425–2432.
Fretwell, S.D. & Lucas, H.L.J., 1970. On territorial behavior and other
factors influencing habitat distribuion in birds. I. Theoretical
development. Acta Biotheoretica, 14, pp.16–36.
35
Garrido, P., Lindqvist, S. & Kjellander, P., 2014. Natural forage
composition decreases deer browsing on Picea abies around
supplemental feeding sites. Scandinavian Journal of Forest Research,
29(3), pp.234–242.
Gehring, T.M. & Swihart, R.K., 2003. Body size, niche breadth, and
ecologically scaled responses to habitat fragmentation: Mammalian
predators in an agricultural landscape. Biological Conservation,
109(2), pp.283–295.
Gidenne, T., 2003. Fibres in rabbit feeding for digestive troubles prevention:
Respective role of low-digested and digestible fibre. Livestock
Production Science, 81(2-3), pp.105–117.
Gordon, I.J., Hester, A.J. & Festa-Bianchet, M., 2004. The management of
wild large herbivores to meet economic, conservation and
environmental objectives. Journal of Applied Ecology, 41(6), pp.1021–
1031.
Gross, J.E. et al., 1995. Movement rules for herbivores in spatially
heterogeneous environments: responses to small scale pattern.
Landscape Ecology, 10(4), pp.209–217.
Grünewald, T. et al., 2013. Statistical modelling of the snow depth
distribution in open alpine terrain. Hydrology and Earth System
Sciences, 17, pp.3005–3021.
Guirado, M., Pino, J. & Rodà, F., 2006. Understorey plant species richness
and composition in metropolitan forest archipelagos: effects of forest
size, adjacent land use and distance to the edge. Global Ecology and
Biogeography, 15(1), pp.50–62.
Gundersen, H., Andreassen, H.P. & Storaas, T., 2004. Supplemental feeding
of migratory moose Alces alces: forest damage at two spatial scales.
Wildlife Biology, 10, pp.213–223.
Hahn, D.C. & Hatfield, J.S., 1995. Parasitism at the landscape scale:
Cowbirds prefer forests. Conservation Biology, 9(6), pp.1415–1424.
36
Hanhimäki, S., 1989. Induced resistance in mountain birch: defence against
leaf-chewing insect guild and herbivore competition. Oecologia, 81(2),
pp.242–248.
Harper, K.A. et al., 2005. Edge influence on forest structure and
composition in fragmented landscapes. Conservation Biology, 19(3),
pp.768–782.
Harvey, L. & Fortin, D., 2013. Spatial heterogeneity in the strength of plantherbivore interactions under predation risk: the tale of bison foraging in
wolf country. PloS one, 8(9), p.e73324.
Heggberget, T.M., Gaare, E. & Ball, J.P., 2002. Reindeer (Rangifer
tarandus) and climate change: Importance of winter forage. Rangifer,
22(1), pp.13–31.
Herkert, J.R., 1994. The effects of habitat fragmentation on midwestern
grassland bird communities. Ecological Applications, 4(3), pp.461–
471.
Hewson, R., 1976. Grazing by mountain hares Lepus timidus L., red deer
Cervus elaphus L. and red grouse Lagopus L. scoticus on heather
moorland in north-east Scotland. Journal of Applied Ecology, 13(3),
pp.657–666.
Hewson, R. & Hinge, M.D.C., 1990. Characteristics of the home range of
mountain hares Lepus timidus. Journal of Applied Ecology, 27,
pp.195–195.
Hintz, H.F., Schryver, H.F. & Stevens, C.E., 1978. Digestion and absorption
in the hindgut of nonruminant herbivores. Journal of Animal Science,
46, pp.1803–1807.
Hirakawa, H., 2001. Coprophagy in leporids and other mammalian
herbivores. Mammal Review, 31, pp.61–80.
Hjeljord, O., Sundstøl, F. & Haagenrud, H., 1982. The nutritional value of
browse to moose. The Journal of Wildlife Management, 2, pp.333–343.
Hjältén, J. & Palo, R.T., 1992. Selection of deciduous trees by free ranging
voles and hares in relation to plant chemistry. Oikos, 63, pp.477–484.
37
Hodar, J.A. & Palo, R.T., 1997. Feeding by vertebrate herbivores in a
chemically heterogeneous environment. Ecoscience, 4, pp.304–310.
Hodder, D.P., Rea, R. V. & Crowley, S.M., 2013. Diet content and overlap
of sympatric mule deer (Odocoileus hemionus), moose (Alces alces),
and elk (Cervus elaphus) during a deep snow winter in Northcentral
British Columbia, Canada. Canadian Wildlife Biology and
Management, 2, pp.43–50.
Hofmann, R.R., 1989. Evolutionary steps of ecophysiological adaptation
and diversification of ruminants: a comparative view of their digestive
system. Oecologia, 78(4), pp.443–457.
Holmgren, B. & Tjus, M., 1996. Summer air temperatures and tree line
dynamics at Abisko. Ecological Bulletins, 45, pp.159–169.
Huitu, O. et al., 2003. Winter food supply limits growth of northern vole
populations in the absence of predation. Ecology, 84(8), pp.2108–2118.
Hulbert, I.A., Iason, G.R. & Mayes, R.W., 2001. The flexibility of an
intermediate feeder: Dietary selection by mountain hares measured
using faecal n-alkanes. Oecologia, 129(2), pp.197–205.
Hulbert, I.A.R. et al., 1996. Home-range sizes in a stratified upland
landscape of two lagomorphs with different feeding strategies. Journal
of Applied Ecology, 33, pp.1479–1488.
Hulbert, I.A.R. & Andersen, R., 2001. Food competition between a large
ruminant and a small hindgut fermentor: the case of the roe deer and
mountain hare. Oecologia, 128, pp.499–508.
Iason, G., 2005. The role of plant secondary metabolites in mammalian
herbivory: ecological perspectives. Proceedings of the Nutrition
Society, 64(01), pp.123–131.
Iason, G.R. & Van Wieren, S.E., 1999. Digestive and ingestive adaptations
of mammalian herbivores to low-quality forage. In H. Olff, V. K.
Brown, & R. H. Drent, eds. Herbivores: between plants and predators.
Oxford: Blackwell, pp. 337–369.
38
Jacob, J. & Brown, J.S., 2000. Microhabitat use, giving-up densities and
temporal activity as short- and long-term anti-predator behaviors in
common voles. Oikos, 91, pp.131–138.
Janis, C.M., 1976. The evolutionary strategy of the Equidae and the origins
of rumen and cecal digestion. Evolution, 30(4), pp.757–774.
Johannessen, V. & Samset, E., 1994. Summer diet of the mountain hare
(lepus timidus L) in a low-alpine area in southern Norway. Canadian
Journal of Zoology, 72(4), pp.652–657.
Johnson, C.J., Parker, K.L. & Heard, D.C., 2001. Foraging across a variable
landscape: Behavioral decisions made by woodland caribou at multiple
spatial scales. Oecologia, 127(4), pp.590–602.
Jonasson, C. et al., 2012. Environmental monitoring and research in the
Abisko area-an overview. Ambio, 41(SUPPL.3), pp.178–186.
Kauhala, K., Hiltunen, M. & Salonen, T., 2005. Home ranges of mountain
hares Lepus timidus in boreal forests of Finland. Wildlife Biology,
11(3), pp.193–200.
Kleiber, M., 1932. Body size and metabolism. Hilgardia, 6, pp.315–351.
Kohler, J. et al., 2006. A long-term Arctic snow depth record from Abisko,
northern Sweden, 1913–2004. Polar Research, 25, pp.91–113.
Kotliar, N.B. & Wiens, J.A., 1990. Multiple Scales of Patchiness and Patch
Structure: A Hierarchical Framework for the Study of Heterogeneity.
Oikos, 59(2), pp.253–260.
Krebs, C.J. et al., 1995. Impact of food and predation on the snowshoe hare
cycle. Science (New York, N.Y.), 269(5227), pp.1112–1115.
Krebs, J.R., Ryan, J.C. & Charnov, E.L., 1974. Hunting by expectation or
optimal foraging? A study of patch use by chickadees. Animal
Behaviour, 22, pp.953–964.
Kullman, L. & Öberg, L., 2009. Post-Little Ice Age tree line rise and climate
warming in the Swedish Scandes: A landscape ecological perspective.
Journal of Ecology, 97(3), pp.415–429.
39
Kullman, L. & Öberg, L., 2015. Post-Little Ice Age tree line rise and climate
warming in the Swedish Scandes: a landscape ecological perspective.
Journal of Ecology, 97(3), pp.415–429.
Kumpula, J., 2001. Winter grazing of reindeer in woodland lichen pasture:
effect of lichen availability on the condition of reindeer. Small
Ruminant Research, 39(2), pp.121–130.
Laca, E., Shipley, L. & Reid, E., 2001. Structural anti-quality characteristics
of range and pasture plants. Journal of Range Management, 54(July),
pp.413–419.
Laca, E.A. et al., 2010. Allometry and spatial scales of foraging in
mammalian herbivores. Ecology Letters, 13, pp.311–320.
Lechner, I. et al., 2010. Differential passage of fluids and different-sized
particles in fistulated oxen (Bos primigenius f. taurus), muskoxen
(Ovibos moschatus), reindeer (Rangifer tarandus) and moose (Alces
alces): Rumen particle size discrimination is independent from
contents. Comparative Biochemistry and Physiology. Part AMolecular and Integrative Physiology, 155, pp.211–222.
Legendre, P. et al., 2002. The consequences of spatial structure for the
design and analysis of ecological field surveys. Ecography, 25,
pp.601–615.
Legendre, P. & Fortin, M., 1989. Spatial pattern and ecological analysis.
Vegetatio, 80, pp.107–138.
Lehtilä, K. et al., 2000. Allocation of resources within mountain birch
canopy after simulated winter browsing. Oikos, 90(1), pp.160–170.
Lehtonen, J. & Heikkinen, R.K., 1995. On the recovery of mountain birch
after Epirrita damage in Finnish Lapland, with a particular emphasis on
reindeer grazing. Ecoscience, 2(4), pp.349–356.
Leopold, A., 1987. Game Management, University of Wisconsin Press.
Li, C.Y. et al., 2003. Photoperiodic control of growth, cold acclimation and
dormancy development in silver birch (Betula pendula) ecotypes.
Physiologia Plantarum, 117(2), pp.206–212.
40
Lindlöf, B., 1980. Some aspects of ecology in hares, Thesis, Dept. of Zool,
University of Stockholm.
Ludwig, M. et al., 2012. Landscape-moderated bird nest predation in hedges
and forest edges. Acta Oecologica, 45, pp.50–56.
Lundberg, P. & Palo, R.T., 1993. Resource use, plant defenses, and optimal
digestion in ruminants. Oikos, 68(2), pp.224–228.
Lundberg, P., Åström, M. & Danell, K., 1990. An experimental test of
frequency-dependent food selection: Winter browsing by moose.
Holarctic Ecology, 13, pp.177–182.
MacArthur, R.H. & Pianka, E.R., 1966. On optimal use of a patchy
environment. The American Naturalist, 100(916), pp.603–609.
Magura, T., 2002. Carabids and forest edge: Spatial pattern and edge effect.
Forest Ecology and Management, 157(1-3), pp.23–37.
Marshall, H.H. et al., 2013. How do foragers decide when to leave a patch?
A test of alternative models under natural and experimental conditions.
The Journal of animal ecology, 82(4), pp.894–902.
Mathisen, K.M. & Skarpe, C., 2011. Cascading effects of moose (Alces
alces) management on birds. Ecological Research, 26(3), pp.563–574.
McNair, J.N., 1982. Optimal giving-up times and the marginal value
theorem. The American Naturalist, 119(4), pp.511–529.
Merkle, J.A., Fortin, D. & Morales, J.M., 2014. A memory-based foraging
tactic reveals an adaptive mechanism for restricted space use. Ecology
Letters, 17(8), pp.924–931.
Miller, J.A., 2012. Species distribution models: spatial autocorrelation and
non-stationarity. Progress in Physical Geography, 36(5), pp.681–692.
Milligan, H.T. & Koricheva, J., 2013. Effects of tree species richness and
composition on moose winter browsing damage and foraging
selectivity: an experimental study. The Journal of Animal Ecology, 82,
pp.739–748.
41
Moen, R., Pastor, J. & Cohen, Y., 1997. A spatially explicit model of moose
foraging and energetics. Ecology, 78(2), pp.505–521.
Muiruri, E.W. et al., 2015. Moose browsing alters tree diversity effects on
birch growth and insect herbivory. Functional Ecology, 29(5), pp.724–
735.
Månsson, J. et al., 2007. Moose browsing and forage availability: a scaledependent relationship? Canadian Journal of Zoology, 85, pp.372–380.
Månsson, J. et al., 2012. Spatial and temporal predictions of moose winter
distribution. Oecologia, 170(2), pp.411–419.
Nagy, K.A., 2005. Field metabolic rate and body size. Journal of
Experimental Biology, 208, pp.1621–1625.
Newey, S. et al., 2010. Population and individual level effects of overwinter supplementary feeding mountain hares. Journal of Zoology,
282, pp.214–220.
Nordengren, C., Hofgaard, A. & Ball, J.P., 2003. Availability and quality of
herbivore winter browse in relation to tree height and snow depth.
Annales Zoologici Fennici, 40, pp.305–314.
Nyström, A., 1980. Selection and consumption of winter browse by moose
calves. Journal of Wildlife Management, 44(2), pp.463–468.
Ohashi, H. & Hoshino, Y., 2014. Disturbance by large herbivores alters the
relative importance of the ecological processes that influence the
assembly pattern in heterogeneous meta-communities. Ecology and
Evolution, 4(6), pp.766–775.
Olofsson, J. et al., 2009. Herbivores inhibit climate-driven shrub expansion
on the tundra. Global Change Biology, 15(11), pp.2681–2693.
Olofsson, J. & Strengbom, J., 2000. Response of galling invertebrates on
Salix lanata to reindeer herbivory. Oikos, 91(3), pp.493–498.
Olsson, J. et al., 2012. Landscape and substrate properties affect species
richness and community composition of saproxylic beetles. Forest
Ecology and Management, 286, pp.108–120.
42
Owen-Smith, N., 2014. Spatial ecology of large herbivore populations.
Ecography, 37(5), pp.416–430.
Owen-Smith, N., Fryxell, J.M. & Merrill, E.H., 2010. Foraging theory
upscaled: the behavioural ecology of herbivore movement.
Philosophical Transactions of the Royal Society of London - Series B:
Biological Sciences, 365, pp.2267–2278.
Owen-Smith, N. & Novellie, P., 1982. What should a clever ungulate eat?
The American Naturalist, 119(2), pp.151–178.
Palo, R.T., 1984. Distribution of birch (Betula SPP.), willow (Salix SPP.),
and poplar (Populus SPP.) secondary metabolites and their potential
role as chemical defense against herbivores. Journal of Chemical
Ecology, 10(3), pp.499–520.
Palo, R.T., Bergström, R. & Danell, K., 1992. Digestibility, distribution of
phenols, and fiber at different twig diameters of birch in winter.
Implication for browsers. Oikos, 65, pp.450–454.
Parker, G.A. & Stuart, R.A., 1976. Animal behavior as a strategy optimizer:
evolution of resource assessment strategies and optimal emigration
thresholds. The American Naturalist, 110(976), pp.1055–1076.
Pastor, J. et al., 1999. Further development of the Spalinger-Hobbs
mechanistic foraging model for free-ranging moose. Canadian Journal
of Zoology, 77, pp.1505–1512.
Pedersen, S. et al., 2014. Small mammal responses to moose supplementary
winter feeding. European Journal of Wildlife Research, 60, pp.527–
534.
Pehrson, Å., 1983a. Caecotrophy in caged mountain hares (Lepus timidus).
Journal of Zoology, 199(4), pp.563–574.
Pehrson, Å., 1983b. Digestibility and retension of food components in caged
mountain hares Lepus timidus during the winter. Holarctic Ecology,
6(4), pp.395–403.
Pehrson, Å., 1979. Winter food consumption and digestibility in caged
mountian hares. In K. Myers & C. D. MacInnes, eds. Proceedings of
43
the World Lagomorph Conference. Guelph University Press, pp. 732–
742.
Pond, K.R., Ellis, W.C. & Akin, D.E., 1984. Ingestive mastication and
fragmentation of forages. Journal of Animal Science, 58(6), pp.1567–
1574.
Pulliainen, E., 1982. Habitat selection and fluctuations in numbers in a
population of the arctic hare (Lepus timidus) on a subarctic fell in
Finnish forest Lapland. Z. Saugetierkd, 47(3), pp.168–174.
Pulliainen, E. & Tunkkari, P.S., 1987. Winter diet, habitat selection and
fluctuation of a mountain hare Lepus timidus population in Finnish
Forest Lapland. Ecography, 10(4), pp.261–267.
Putman, R.J. & Staines, B.W., 2004. Supplementary winter feeding of wild
red deer Cervus elaphus in Europe and North America: justifications,
feeding practice and effectiveness. Mammal Review, 34(4), pp.285–
306.
Rastetter, E.B. et al., 2003. Using mechanistic models to scale ecological
processes across space and time. BioScience, 53(1), pp.68–76.
Rehnus, M., 2014. The 24-hour cycle of the mountain hare Lepus timidus
Linnaeus, 1758. Der Zoologische Garten, 83, pp.140–145.
Renecker, L.A. & Hudson, R.J., 1989. Seasonal activity budgets of moose in
aspen-dominated boreal forests. Journal of Wildlife Management, 53,
pp.296–302.
Renecker, L.A. & Hudson, R.J., 1986. Seasonal foraging rates of freeranging moose. Journal of Wildlife Management, 50(1), pp.143–147.
Reynolds, A.M., 2012. Fitness-maximizing foragers can use information
about patch quality to decide how to search for and within patches:
optimal Levy walk searching patterns from optimal foraging theory.
Journal of The Royal Society Interface, 9(72), pp.1568–1575.
Rousi, M., Tahvanainen, J. & Uotila, I., 1991. A Mechanism of resistance to
hare browsing in winter-dormant European white birch (Betula
pendula). American Naturalist, 137, pp.64–82.
44
Rundqvist, S. et al., 2011. Tree and shrub expansion over the past 34 years
at the tree-line near Abisko, Sweden. Ambio, 40, pp.683–692.
Sæther, B.E. & Gravem, A.J., 1988. Annual variation in winter body
condition of Norwegian moose calves. Journal of Wildlife
Management, 52(2), pp.333–336.
Sahlsten, J. et al., 2010. Can supplementary feeding be used to redistribute
moose Alces alces? Wildlife Biology, 16, pp.85–92.
Saracco, J.F., Collazo, J.A. & Groom, M.J., 2004. How do frugivores track
resources? Insights from spatial analyses of bird foraging in a tropical
forest. Oecologia, 139, pp.235–245.
Schneider, D.C., 2001. The rise of the concept of scale in ecology.
BioScience, 51(7), pp.545–553.
Searle, K.R., Hobbs, N.T. & Shipley, L.A., 2005. Should I stay or should I
go? Patch departure decisions by herbivores at multiple scales. Oikos,
111(3), pp.417–424.
Seiler, A., 2005. Predicting locations of moose-vehicle collisions in
Sweden. Journal of Applied Ecology, 42(2), pp.371–382.
Senn, J. & Haukioja, E., 1994. Reactions of the mountain birch to bud
removal: effects of severity and timing, and implications for herbivore.
Functional Ecology, 8(4), pp.494–501.
Shipley, L., 1999. Grazers and browsers: how digestive morphology affects
diet selection. In K. L. Lanchbaugh, K. D. Sanders, & J. C. Mosley,
eds. Grazing behavior of livestock and wildlife. Moscow: Idaho forest,
Wildlife and Range Experimental Station Bulletin 70. University of
Idaho, pp. 20–27.
Shipley, L.A., 2010. Fifty years of food and foraging in moose: lessons in
ecology from a model herbivore. Alces, 46, pp.1–13.
Shipley, L.A., 2007. The influence of bite size on foraging at larger spatial
and temporal scales by mammalian herbivores. Oikos, 116(12),
pp.1964–1974.
45
Shipley, L.A. et al., 1994. The scaling of intake rate in mammalian
herbivores. The American Naturalist, 143(6), pp.1055–1082.
Shipley, L.A., Blomquist, S. & Danell, K., 1998. Diet choices made by freeranging moose in northern Sweden in relation to plant distribution,
chemistry, and morphology. Canadian Journal of Zoology, 76(9),
pp.1722–1733.
Shipley, L.A., Forbey, J.S. & Moore, B.D., 2009. Revisiting the dietary
niche: when is a mammalian herbivore a specialist? Integrative and
Comparative Biology, 49(3), pp.274–290.
Sievert, P. & Keith, L., 1985. Survival of snowshoe hares at a geographic
range boundary. The Journal of wildlife management, 49(4), pp.854–
866.
Skogland, T., 1985. The effects of density-dependent resource limitations on
the demography of wild reindeer. Journal of Animal Ecology, 54,
pp.359–374.
Skogland, T., 1984. Wild reindeer foraging-niche organization. Holarctic
Ecology, 7, pp.345–379.
Van Soest, P.J., 1996. Allometry and ecology of feeding behavior and
digestive capacity in herbivores: a review. Zoo Biology, 15, pp.455–
479.
Van Soest, P.J., 1967. Development of a comprehensive system of feed
analyses and its application to forages. Journal of Animal Science,
26(1), pp.119–128.
Van Soest, P.J., 1994. Nutritional ecology of the ruminant, Ithaca, New
York: Cornell University Press.
Sorensen, A., Van Beest, F.M. & Brook, R.K., 2014. Impacts of wildlife
baiting and supplemental feeding on infectious disease transmission
risk: A synthesis of knowledge. Preventive Veterinary Medicine, 113,
pp.356–363.
46
Spalinger, D.E. & Hobbs, N.T., 1992. Mechanisms of foraging in
mammalian herbivores: new models of functional response. The
American naturalist, 140(2), pp.325–348.
Stark, S., Julkunen-Tiitto, R. & Kumpula, J., 2007. Ecological role of
reindeer summer browsing in the mountain birch (Betula pubescens
ssp. czerepanovii) forests: effects on plant defense, litter
decomposition, and soil nutrient cycling. Oecologia, 151(3), pp.486–
498.
Stephens, D.W. & Krebs, J.R., 1986. Foraging Theory, Princeton: Princeton
University Press.
Steuer, P. et al., 2013. Fibre digestibility in large herbivores as related to
digestion type and body mass- an in vitro approach. Comparative
Biochemistry and Physiology - A Molecular and Integrative
Physiology, 164(2), pp.319–326.
Stewart, A. & Komers, P.E., 2012. Testing the ideal free distribution
hypothesis: moose response to changes in habitat amount. ISRN
Ecology, 2012, pp.1–8.
Steyaert, S.M.J.G. et al., 2014. Behavioral correlates of supplementary
feeding of wildlife: can general conclusions be drawn? Basic and
Applied Ecology, 15, pp.669–676.
Stolter, C. et al., 2005. Winter browsing of moose on two different willow
species: food selection in relation to plant chemistry and plant
response. Canadian Journal of Zoology, 819, pp.807–819.
Stöcklin, J. & Körner, C., 1999. Recruitment and mortality of Pinus
sylvestris near the nordic treeline: the role of climatic change and
herbivory. Ecological Bulletins, 47, pp.168–177.
Sutherland, W.J., 2006. Predicting the ecological consequences of
environmental change: a review of the methods. Journal of Applied
Ecology, 43(4), pp.599–616.
Sweanor, P.Y. & Sandegren, F., 1989. Winter range philopatry of seasonally
migratory moose. Journal of Applied Ecology, 26, pp.25–34.
47
Telfer, E.S. & Kelsall, J.P., 1984. Adaptation of some large North American
mammals for survival in snow. Ecology, 65(6), pp.1828–1834.
Tenow, O., 1996. Hazards to a mountain birch forest- Abisko in perspective.
Ecological Bulletins, 45, pp.104–114.
Tenow, O. & Bylund, H., 2000. Recovery of a Betula pubescens forest in
northern Sweden after severe defoliation by Epirrita autumnata.
Journal of Vegetation Science, 11, pp.855–862.
Thirgood, S.J. & Hewson, R., 1987. Shelter characteristics of mountain hare
resting sites. Holarctic Ecology, 10(4), pp.294–298.
Thomas, V.G., 1987. Similar winter energy strategies of grouse, hares and
rabbits in northern biomes. Oikos, 50, pp.206–212.
Tømmervik, H. et al., 2009. Above ground biomass changes in the mountain
birch forests and mountain heaths of Finnmarksvidda, northern
Norway, in the period 1957-2006. Forest Ecology and Management,
257(1), pp.244–257.
Ungar, E.D. & Noy-Meir, I., 1988. Herbage intake in relation to availability
and sward structure: grazing processes and optimal foraging. Journal
of Applied Ecology, 25(3), pp.1045–1062.
WallisDeVries, M.F., Laca, E.A. & Demment, M.W., 1999. The importance
of scale of patchiness for selectivity in grazing herbivores. Oecologia,
121(3), pp.355–363.
Valone, T.J. & Brown, J.S., 1989. Measuring patch assessment abilities of
desert granivores. Ecology, 70, pp.1800–1810.
Wam, H.K. & Hjeljord, O., 2010. Moose summer and winter diets along a
large scale gradient of forage availability in southern Norway.
European Journal of Wildlife Research, 56, pp.745–755.
Wang, X., Blanchet, F.G. & Koper, N., 2014. Measuring habitat
fragmentation: an evaluation of landscape pattern metrics. Methods in
Ecology and Evolution, 5(7), pp.634–646.
48
Veen, G.F., Geuverink, E. & Olff, H., 2012. Large grazers modify effects of
aboveground-belowground interactions on small-scale plant
community composition. Oecologia, 168(2), pp.511–518.
Weih, M. & Karlsson, P.S., 2002. Low winter soil temperature affects
summertime nutrient uptake capacity and growth rate of mountain
birch seedlings in the subarctic, Swedish lapland. Arctic Antarctic and
Alpine Research, 34, pp.434–439.
Welch, J.G., 1982. Rumination, particle size and passage from the rumen.
Journal of animal science, 54(4), pp.885–894.
Vidus-Rosin, A. et al., 2012. Habitat selection and segregation by two
sympatric lagomorphs: the case of European hares (Lepus europaeus )
and Eastern cottontails (Sylvilagus floridanus ) in northern Italy. Acta
Theriologica, 57(4), pp.295–304.
Wiens, J., 1989. Spatial scaling in ecology. Functional Ecology, 3, pp.385–
397.
Williams-Linera, G., 1990. Vegetation structure and environmental
conditions of forest edges in Panama. Journal of Ecology, 78(2),
pp.356–373.
Wilson, R.P. et al., 2013. Turn costs change the value of animal search
paths. Ecology Letters, 16(9), pp.1145–1150.
Vivås, H.J. & Sæther, B.E., 1987. Interactions between a generalist
herbivore, the moose Alces alces, and its food resources: an
experimental study of winter foraging behaviour in relation to browse
availability. Journal of Animal Ecology, 56, pp.509–520.
Zangerl, A.R. & Bazzaz, F.A., 1992. Theory and pattern in plant defense
allocation. In R. S. Fritz & E. L. Simms, eds. Plant resistance to
herbivores and pathogens: ecology, evolution, and genetics. Chicago:
University of Chicago Press, pp. 363–391.
Öhmark, S.M., Iason, G.R. & Palo, R.T., 2015. Spatially segregated
foraging patterns of moose (Alces alces) and mountain hare (Lepus
timidus) in a subarctic landscape: different tables in the same
restaurant? Canadian Journal of Zoology, 93, pp.391–396.
49