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\begin{document}

\title{Prescribed Fire in the Nelchina Basin: A Case Study for Managing Moose
Population}



\author[1]{Katie Anderson}%
\author[2]{Donald Spalinger}%
\author[3]{William Collins}%
\affil[1]{Washington State University}%
\affil[2]{University of Alaska Anchorage}%
\affil[3]{State of Alaska Department of Fish and Game}%


\vspace{-1em}



  
  \date{May 18, 2024}


\begingroup
\let\center\flushleft
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\maketitle
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\selectlanguage{english}
\begin{abstract}
The Nelchina Basin, located west of Glenallen, AK provides important
moose (Alces alces) habitat throughout the year. However, previous
research in this area has shown that the moose populations appear to be
nutritionally limited by the available forage. The Nelchina Basin was
deemed an intensive management unit to increase moose populations
through predator control efforts and prescribed fires to increase the
amount of available forage, including the 2004 Alphabet Hills fire. We
quantified the available digestible energy (DE) and digestible protein
(DP) during the summer of 2018 and 2019, as well as the winter in
between, and availability of forages for moose within the burn perimeter
and the adjacent unburned forest during the summer of 2019. We found
that total canopy cover of the primary forage species was lower in the
burned areas than in the adjacent unburned forest habitats. DP
concentration was not significantly different between forested and
burned sites, and DE and DP content varied across the summer and winter
sampling season. We also found a significant difference in DE and DP
across the two sampling years. Although others have shown a positive
effect of wildfire for herbivore populations, we found that some areas,
including the Alphabet Hills area, may not be suitably adapted to
benefit from the quick release of nutrients after fire and may not
allocate more resources to biomass as previously expected. This project
highlights the importance of research that quantifies both the
availability of and the quantity of available food resources for
herbivores.%
\end{abstract}%



\sloppy


\textbf{Prescribed Fire in the Nelchina Basin: A Case Study for Managing
Moose Population}

\section*{Abstract}

{\label{abstract}}

The Nelchina Basin, located west of Glenallen, AK provides important
moose (\emph{Alces alces} ) habitat throughout the year. However,
previous research in this area has shown that the moose populations
appear to be nutritionally limited by the available forage. The Nelchina
Basin was deemed an intensive management unit to increase moose
populations through predator control efforts and prescribed fires to
increase the amount of available forage, including the 2004 Alphabet
Hills fire. We quantified the available digestible energy (DE) and
digestible protein (DP) during the summer of 2018 and 2019, as well as
the winter in between, and availability of forages for moose within the
burn perimeter and the adjacent unburned forest during the summer of
2019. We found that total canopy cover of the primary forage species was
lower in the burned areas than in the adjacent unburned forest habitats.
DP concentration was not significantly different between forested and
burned sites, and DE and DP content varied across the summer and winter
sampling season. We also found a significant difference in DE and DP
across the two sampling years. Although others have shown a positive
effect of wildfire for herbivore populations, we found that some areas,
including the Alphabet Hills area, may not be suitably adapted to
benefit from the quick release of nutrients after fire and may not
allocate more resources to biomass as previously expected. This project
highlights the importance of research that quantifies both the
availability of and the quantity of available food resources for
herbivores.

\section*{Introduction}

{\label{introduction}}

Ecologists and wildlife managers generally agree that throughout the
world, large-scale disturbance, such as wildfire, can be beneficial for
species of large herbivores that are adapted to seral plant communities.
Burned plots in states like Colorado and Nevada have been shown to
increase crude protein intake for mule deer (\emph{Odocoileus heminonus}
) and bighorn sheep (\emph{Ovis canadensis} ) in grassland and montane
shrub communities (Hobbs and Spowart 1984). Higher abundances of bison
(\emph{Bison bison} ) were found in recently burned watersheds within
the Konza Prairie Research Natural Area in Northern Kansas (Knapp et al.
1999). In summer, these herbivores select grasses and herbaceous plants
that respond rapidly to the release of post-fire nutrient deposits
(Boerner 1982). In boreal forest ecosystems, post-fire stands are
commonly assumed to support higher populations of moose (\emph{Alces
alces} ) than adjacent unburned stands, but quantification of the
impacts of fire on moose population productivity is limited. Fire, both
natural and prescribed, is considered beneficial to moose because
deciduous woody browses and herbaceous foods (e.g., \emph{Chamerion
angustifolium} ) respond rapidly to post-fire conditions, increasing
food abundance significantly (Landhausser and Wein 1993). Studies
focusing on vegetation after fire show high variability with respect to
both the biomass productivity and the species composition that
regenerates (Rau et al. 2008, Johnstone et al. 2010).

Although there is significant evidence suggesting that browse biomass
density increases after fire, there is little regarding the effect of
fire on plant chemistry after fire (Bryant et al. 1983, Maier et al.
2005, Joly et al. 2016, Brown et al. 2018). Alteration of plant
chemistry after fire could have dramatic effects on the overall
palatability, and therefore the nutritional quality, of browse species.
Globally, herbivores are limited by the availability of nitrogen, the
element necessary for making protein and therefore building muscle.
Nitrogen concentration in boreal plants is a limiting factor for the
plants themselves and may be a limiting factor for herbivore growth and
reproductive success (McArt et al. 2009, Gundale et al. 2010). Low
resource environments, including the boreal forest, are dominated by
plants such as evergreens that are slow growing, even when provided with
an optimal supply of resources (Chapin, 1991, Gundale et al. 2010). Slow
growth in these plants is attributed to an inability to quickly uptake
nutrients, a higher allocation to survivorship traits such as chemical
defenses, and internal constraints to growth (Chapin, 1991). Due to
these growth limitations, nutrients may be leached out of a system
before the species has the chance to sequester them (Chapin, 1991,
Gundale et al. 2010), although fire has been found to increase nutrient
availability. Deciduous species located in nutrient-limited stands have
a greater proportion of secondary metabolites than in more productive
ecotones, making them less usable by associated herbivores (Gundale et
al. 2010). This defense strategy makes these plants less palatable to
herbivores.

Nutritional carrying capacity is limited by two elements of a habitat:
forage availability and forage quality. Both of which may be
significantly altered after a disturbance such as fire. This potential
tradeoff between higher availability of browse and potentially lower
quality could affect moose productivity and movement. Hobbs and Swift
(1985) showed that in high biomass areas nutrient intake is limited by
the nutritional quality of the food source. If browse availability
increases significantly in burned stands, but the nutritional quality
declines, then moose density may increase, at the cost of per capita
fitness (Hobbs and Swift 1985, 1988).

The response of moose to fire depends on browse biomass and diversity,
and nutritional quality, including plant defenses (Hobbs and Swift 1985,
Hobbs 2003). We measured these funda-mental characteristics in a
16-year-old prescribed burn in the Nelchina Basin and in its adjacent
unburned forests. The Nelchina Basin located west of Glenallen, AK,
supports one of the highest moose harvests in the state (Boertje et al.
2007), drawing in hunters from throughout south-central and interior
Alaska (Figure 1).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1:} The Alphabet Hills fire, burned in 2004 for habitat
management, is located west of Glenallen, AK. The map on the left shows
the fire's location in relation to the total fire history of Alaska
while the map on the right shows the burn perimeter, the fire intensity
readings (MTBS.gov), and the sampling points in purple. The legend shows
the range in severity from high to low, including areas that were not
processed or masked, as well as the acreage considered to be within each
category.

Although moose in this area have access to large amounts of habitat,
they often show indications of nutritional stress. Twinning rates and
age of first parturition are significantly lower than their reproductive
capacity (Testa 2004, Boertje et al. 2007). This led to an intensive
management plan that includes predator controls and habitat management
strategies such as prescribed burns. The Alphabet Hills, within the
Nelchina Basin, was burned in 2004 as part of a management plan to
increase moose habitat. The anticipated increase in moose productivity
was expected to increase harvest opportunity, and to buffer losses to
predation.

Stand succession, and stand quality after fire, is highly dependent on
the pre-fire characteristics of the area as well as fire severity.
Higher intensity fires can volatilize nitrogen that otherwise would be
available to growth of forages and ultimately to the quality of moose
diets (Boerner 1982, Bayley et al. 1992). The volatilization of nitrogen
could be especially important in boreal regions due to the natural
limitation of nitrogen in boreal soils. In addition, the response of
plants to allocating carbon and nitrogen to growth vs defense is likely
dependent upon browsing severity, climate and site conditions, nutrient
availability, and plant competition. Taken together, it is difficult to
predict the impact of natural or prescribed fire on moose populations or
their productivity.

Timing since burn is itself an important factor for moose forage
selection (Brown et al. 2018). Moose are considered near-obligate
browsers, consuming the leaves and terminal twigs of a variety of
deciduous woody trees and shrubs, particularly of the genus Salix.
Hence, they are often associated with successional and riparian
communities where such plants are abundant. In the boreal forest biome,
where moose are most abundant, the climax community is typically
coniferous, and in North America, dominated by black (\emph{Picea
mariana} ) and white spruce (\emph{Picea glauca} ). However, early
successional stages following wildfire in spruce forests are generally
dominated by deciduous browses. Previous studies (Vitousek and Reiners
1975, Regelin et al. 1987, Julianus 2016) have shown that moose appear
to select successional stands that are between 10 to 20 years in age
post disturbance compared to stands that are less than 10 years or
greater than 25 years post disturbance. For younger stands, preferred
species could be small and harder to reach by moose, but, primarily,
snow depth could also limit their use during the winter by burial of
stems and inhibiting movement through an area (Vitousek and Reiners
1975). Deeper snow also correlates with increased selection of riparian
areas and areas at lower elevations that could increase localized
predation risk (Joly et al. 2016). Stand replacement occurs between 30
and 40 years when the dominant species shift from deciduous shrubs to
spruce, and competition with spruce limits the amount of forage in the
area (Regelin et al. 1987, Brown et al. 2018). Studies focusing on
habitat selection show that during the winter, moose did not select for
areas until 10 to 25 years after a disturbance because deciduous stems
were buried by the snow prior to that (Regelin et al. 1987, Joly et al.
2016).

The Alphabet Hills area of the Nelchina Basin is classified as an open
spruce forest/shrub/bog or as an open and closed spruce forest (Viereck
1992, Markon and Walker 1998). These stands are typically characterized
by cold, poorly drained organic soils, and overall low productivity
(Landhausser and Wein 1993, Crevoisier et al. 2007). Alaskan black
spruce fires typically occur every 70 to 125 years, with
replacement/high severity fires that kill 75\% of the upper canopy
occurring in 45 to 85\% of fires (Landhausser and Wein 1993, Crevoisier
et al. 2007). Fire can reduce the overall organic layer thereby
increasing water drainage and limiting water available to plants (Yi et
al. 2009). Post-fire environmental conditions, such as increased UV
exposure, water stress, and nutrient leaching/loss may place additional
stresses on plant growth, which may result in an increase in secondary
defense compounds such as condensed tannins. Condensed tannins are
thought to have originally evolved to protect the plant from water
stress, but they are also made to protect the plant from herbivores
(Herms and Mattson 1992). Tannin concentration is higher in the early
growth stages of browses important for moose which may be a result of
induced chemical defenses of the newest, most productive tissues (Bryant
and Kuropat 1980, Bryant et al. 1983, Herms and Mattson 1992, Spalinger
et al. 2010). High condensed tannin concentrations in conjunction with
relatively low protein concentrations in some plants can result in net
negative protein gain for an herbivore due to its ability to bind both
plant proteins and animal/microbial proteins endogenous to the GI tract
(Spalinger et al. 2010, Tharayil et al. 2011, Adamczyk et al. 2017).

In burned habitats, defensive compounds may also increase because of
environmental stresses that change the resource allocation patterns of
plants. For example, increased solar radiation and more xeric soil
conditions can induce water stress in summer (Herms and Mattson 1992,
Gundale et al. 2010), leading to increases in oxidative stress
responses, including polyphenolic concentrations (Chapin, 1991, Rau et
al. 2008, Tharayil et al. 2011). Heightened solar radiation can also
slow overall photosynthetic rate due to a build-up in sucrose-levels
that limits the movement of carbon dioxide (Sweet and Wareing 1966). The
diminished photosynthetic rate limits the productivity of the tissues
which reduces the overall quality available for herbivores (Sweet and
Wareing 1966). Increased tannin concentration may affect the microbiome
of the rumen which ruminant species rely on to digest woody browse
(Solden et al. 2017). This may result in lower nutritional quality,
particularly nitrogen availability, to large herbivores, potentially
limiting animal productivity (McArt et al. 2009). High concentrations of
condensed tannins can also further limit nitrogen availability for
plants in boreal forests by binding to amino acids and/or soil microbial
exoenzymes in the soil once deposited by fire, creating a positive
feedback loop (Gundale et al. 2010). This therefore limits uptake by
microorganisms of both proteins, and potentially carbon as well (Gundale
et al. 2010).

Development of seral vegetation following fire may attract an
overabundance of moose, leading to a reduction in the overall quality of
those habitats through selective removal of the most nutritional
species. Fire can also redistribute moose to early seral stands, in turn
leading to a reduction of the overall quality of those habitats through
the removal of the most nutritional species (Collins and Schwartz 1998,
Shipley 2010, Collins et al. 2011). Over browsing by moose can result in
a shift in dominant species from preferred species like Salix spp. to
the less nutritious \emph{Betula} spp. (Christie et al. 2015). Reduction
in forage diversity because of over browsing can also reduce the
opportunity for the animal to balance toxin loads. Browsing by moose
also has the potential to keep shrubs within browsing height, making
them easily outcompeted by spruce (Pastor et al. 1988).

The objectives of this study were (1) to test the hypothesis that
wildfire creates compositional and chemical changes in plants in burned
habitats that are beneficial to moose and (2) to examine the potential
tradeoffs between food abundance and quality on nutritional status of
moose.

\textbf{Materials and Methods}

\emph{Study Site}

To examine the impact of fire on availability and nutritional quality of
browses for moose we examined the Alphabet Hills Fire (62.713906N
146.655193W), a prescribed burn intended to enhance moose habitat in the
Nelchina Basin. The burn occurred in the summer of 2004 and its extent
was 152 km2 (Figure 1). The Nelchina Basin is dominated by black spruce
forest interspersed with numerous lakes and small streams. The canopy is
dominated by black spruce with white spruce dispersed intermittently.
The understory is dominated by deciduous browse including diamond leaf
willow (\emph{Salix pulchra} ), Grayleaf willow (\emph{Salix glauca} ),
mountain alder (\emph{Alnus crispa} ), and dwarf birch (\emph{Betula
nana} ). Not only does the area house a large moose population but it is
also home to caribou, who use the burned area in the summer, bears, and
wolves.

\emph{Field Methods}

Sampling sites were randomly selected throughout both the burned and
un-burned habitats within 4 km of Porkchop Lake (Figure 1). In total, 20
sites were placed in the burned habitat and 20 in the forested habitat
(Figure 1). Several of the unburned sites occurred within the burn
perimeter, having escaped the fire. At each sampling site plant samples
were collected from all species that were considered potential browse
species of moose, based on field observations of browsed plants at all
the sites and previous experience from tame animal observations and
browsing studies in the region. At each sampling location, three samples
of the dominant browse species were collected in order to capture the
spatial and individual variation in plant chemistry and nutritional
quality across the burned and unburned habitats. Samples were placed
into coin envelopes or zip lock bags and frozen immediately on dry ice.
Sampling was done in mid-June, mid-July, and mid-August in the summer of
2018, and again in mid-June and mid-August in the summer of 2019 to
capture the seasonal variation and yearly variation in nutritional
quality of the plants.

During August of 2019, we also quantified canopy cover and available
bites of forage at each sampling site using randomly placed point
intercept transects in both habitat types. At each sample point, a
point-cover transect was established to measure canopy cover of each
browse species and the relative frequency of bites available to moose.
Transects were 50 meters in length and oriented along a randomly
selected bearing. At each meter, all species that intercepted meter
marks on the tape measure were recorded, including ground cover and any
overstory species (Elzinga et al. 1998). For species that could appear
in a moose's diets, we also recorded the number and size of the
potential bites that intercepted the point this was used to as a metric
for bite frequency available in the burned/disturbed and forest sites.
Interceptions of potential bites were indicated with the use of a plumb
bob or a periscope.

Winter sampling was done at the same field sampling locations during
March of 2019, as well as new locations accessible by helicopter.
Current annual growth (CYG) of available browse species was clipped and
placed into a zip lock bag and frozen immediately. We also measured the
diameter at the point of browsing for each species consumed by moose in
winter using Bluetooth calipers that were paired with a mobile de-vice.
These measurements guided our subsequent nutritional analyses of the
winter twigs (Shipley and Spalinger 1995, Shipley et al. 1999).

\emph{Lab Methods}

Nutritional analyses were completed at the Alaska Department of Fish and
Game (ADFG) Herbivore Nutrition Laboratory, in Palmer, AK. Digestible
energy and digestible protein of all forage species were quantified
using the methods outlined by Spalinger et al. (2010) and McArt et al
(2006). Vegetation samples collected in the field were subsequently
freeze-dried and ground in a Wiley mill over a 20-mm screen (McArt et
al. 2006). Before being ground, winter twig samples were segregated into
three diameter segments in order to quantify the relationship between
nutritional quality and diameter of the twig. The goal was to divide the
stems into three diameter classes that produced approximately equal
masses with enough sample for the nutritional analyses. Regressions were
then used to predict nutritional quality and bite size from diameter at
point of browsing for any given species.

Nitrogen concentrations were determined using a LECO TruSpec CHN and
Cos-tech CHNOS Analyzer with NIST apple leaves used as quality control
standard for every 10th sample (McArt et al. 2006). Digestible dry
matter of each forage was determined from sequential fiber analysis
using the ANKOM 200 fiber analysis system according to manufacturer's
recommended methods. Neutral detergent fiber (NDF) was determined with a
neutral detergent solution made with sodium sulfite and an acid
detergent solution was used to determine acid detergent fiber (ADF). NDF
is an estimate of the ratio of insoluble fiber of the plant in the cell
wall and the highly digestible cell contents while ADF is a measure of
the cellulose + lignin/cutin concentration (Van Soest 1994, Spalinger et
al. 2010). Samples were then extracted in 72\% sulfuric acid to
determine lignin + cutin concentration (Van Soest 1994, Spalinger et al.
2010). The sulfuric acid residue was then ashed at 500 for 3 hours to
determine the mineral/silica concentration (Van Soest 1994, Spalinger et
al. 2010, Cook et al. 2022). Because of a shift in sequential fiber
values since 2012, we used a modified correction as described in Cook et
al. (2022). Digestible dry matter (DDM) and energy (DE) were
subsequently estimated from equations presented by Spalinger et al.
(Spalinger et al. 2010).

Tannins were extracted in a 50\% methanol solution under high pressure
and temperature in a DionexTM Accelerated Solvent Extractor (ASE-200)
(Close et al. 2003, McArt et al. 2006). The tannin extract was then
diluted with 50\% methanol, mixed with bovine serum albumin (BSA) and
purified with Sephadex G-25. The resulting solution was mixed with
Bradford Protein Reagent and read on a UV-Vis microplate spectrometer at
595 nm to estimate protein precipitating capacity (PPC, mg DSA
precipitated/mg forage DM) (McArt et al. 2006). PPC was then used to
calculate the digestible protein, the percent protein reduction, and
digestible energy of each sample (Robbins et al. 1987, Spalinger et al.
2010).

After freeze-drying, twigs were subdivided into 3 diameter classes for
subsequent nutritional analyses, following the methods outlined above.
After nutritional analyses, mass-diameter and nutrient density -
diameter regressions were computed for each species. From these,
estimates of nutritional quality and bite size were made for field
measured browsed twigs.

\emph{Statistical Analyses}

To test the hypothesis that burned habitat was of nutritionally higher
quality than unburned habitats, we analyzed the nutritional quality data
in a hierarchical fashion. For the analysis, we only used species that
were found in both habitat treatment types. Four species that were only
found in the burned habitat (fireweed, quaking aspen (\emph{Populus
tremuloides} ), little tree willow (\emph{Salix arbusculoides} ), and
sedges) were removed from the analysis, leaving nine different species
to be included in the analysis (\emph{Alnus crispa} ,
\emph{Equisetum}spp., \emph{Salix pulchra} , \emph{S. glauca} , \emph{S.
pseudomyrisinites} , \emph{S. richardsonii} , \emph{Betula nana} ,
\emph{B. glandulosa} , and \emph{B. neoalaskana} ). We first compared
overall nutritional quality of habitats for all forages combined using a
multivariate analysis of variance (MANOVA) with habitat type, month, and
year as covariates. We tested the interaction between habitat type and
month sampled using an ANOVA, with digestible energy, nitrogen
concentration, percent reduction in proteins from tannins, and
digestible protein as dependent variables. We also calculated the
species diversity of each habitat type using the Shannon-Weiner Index
(Eq. 2), where pi is the proportion of total sample represented by
species i, and H is the diversity of each study site.

H=\selectlanguage{english}\selectlanguage{greek}Σ{[}(pi)\selectlanguage{ngerman}×ln(pi){]}. (2)

Comparisons of forest versus burn for individual forage species common
to both sites were done using unpaired t-tests with a Bonferroni
multiple comparison adjustment. All statistical analyses were performed
in R (Marsh et al. 2006), and all comparisons were considered
significantly different at \emph{p} \textless{} 0.05. Individual species
that were found in both burned and unburned habitats, including diamond
leaf willow, dwarf birch, and gray leaf willow, were also compared
individually using unpaired t-tests with a Bonferroni multiple
comparison adjustment to directly compare the two habitat treatment
types.

\textbf{Results}

Over the 2018-2019 field seasons, we sampled the Alphabet Hills burn on
six occasions, five times across the summers of 2018 and 2019 and once
in the winter of 2018-2019. We collected over 500 plant samples, and
measured canopy coverage of moose browses from randomly selected plots
in burned (\emph{n} = 16) and unburned habitats (\emph{n} = 10). We
found that the total canopy cover of moose preferred browses were higher
in forested sampling sites than in burned sites. There was a significant
difference between browse canopy cover in the forest compared to the
burn (forest \% cover = 10\%, SE = 0.019, burn \% cover = 9\%, SE =
0.01; \emph{t} = 19.18, \emph{p} = 0.033) (Figure 2). The burned area
had higher diversity of species (burn H = 1.709, forest H = 1.509) with
four species that were only found in the burned areas including
fireweed, quaking aspen, little tree willow and various mushrooms
(\emph{Boletus} spp.) that are consumed by moose (Figure 2).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2:} Total canopy cover of available browse and forbs for
moose separated by the species and the habitat type.

\emph{Nutritional Quality}

The digestible energy of forage overall decreased throughout summer
following the browse's phenological progression and deposition of fiber
(Figure 3).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Figure 3} : Digestible Energy (kJ/g dry matter) for each
preferred species for a moose during the summer sampling periods,
separated by month and by habitat type where each sample was collected.

Overall, digestible energy decreased by 50\% (June mean = 19.37 kJ/g DM,
SE = 1.96, August mean = 14.07 kJ/g DM, SE = 3.21, \emph{p} \textless{}
0.0001) between June and August for the Alphabet Hills (Table 1).
Average digestible energy was not significantly different between
habitat types (burned mean = 14.87 kJ/g DM, SE = 4.25, forested mean =
15.42 kJ/g DM, SE = 4.32), but the interaction between habitat type and
month (F = 215.7, \emph{p} \textless{} 0.0001) as well as habitat type
and species were both significant (F = 2.86, \emph{p} \textless{}
0.0001). We also found a significant difference in year; 2018 had an
average DE of 17.04 kJ/g DM (SE = 3.06) while 2019 had an average of
13.33 kJ/g DM (SE = 4.46, \emph{p} \textless{} 0.0001).

\textbf{Table 1:} Comparison of average digestible energy (kJ/g DM) of
species appearing in both burned and unburned sites in the Alphabet
Hills, Alaska in June, August, and March\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Mean (SE)}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Diff}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{P-value}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Mean (SE)}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Diff}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{P-value}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Alphabet} \textbf{Hills}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Alphabet} \textbf{Hills}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Burn}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
14.874 (4.245)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{June}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
19.37 (1.958)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Forest}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
15.421 (4.318)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-0.547\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.12\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{August}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
14.074 (3.212)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-5.4\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{March}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
10.589 (1.934)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-3.119\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textless{}0.0001***\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
S. pulchra\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
S. pulchra\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Burn}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
14.416 (4.268)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{June}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
18.824 (1.441)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Forest}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
15.475 (4.259)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-1.059\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
.053\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{August}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
15.17 (2.757)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-4.26\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{March}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
10.832 (1.506)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-4.338\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textless{}0.0001***\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
B. nana\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
B. nana\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Burn}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
13.76 (3.651)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{June}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
18.735 (1.532)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Forest}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
14.421 (4.56)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-0.661\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.33\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{August}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
11.669 (2.559)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-7.066\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{March}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
10.443 (2.073)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-1.226\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textless{}0.0001***\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
S. glauca\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
S. glauca\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Burn}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
14.651 (4.465)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{June}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
18.112 (2.079)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Forest}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
14.789 (2.936)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-0.138\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.91\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{August}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
13.933 (1.998)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-4.179\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{March}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
8.955 (1.961)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-4.978\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textless{}0.0001***\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Digestible protein is a function of nitrogen concentration and the PPC
of tannins. We found that digestible protein was similarly affected by
month and year, just as with nitrogen concentration and tannin effects
individually (Figure 4).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Figure 4:} Apparent digestible protein (g/g DM) recorded for
each species of selected for species moose for the summer sampling
periods. Values are separated by the month and habitat type where each
sample was collected.

For all species combined, digestible protein was significantly lower in
August than in June (August = 0.023 g/g DM, SE = 0.032, June mean =
0.155 g/g DM, SE = 0.053, \emph{p} \textless{} 0.0001) (Table 2).

Digestible protein was significantly higher in 2018 at 0.78 g/g DM (SE =
0.062) than in 2019 at 0.045 g/g DM (SE = 0.085,
\emph{p}\textless{}0.0001). Digestible protein was not significantly
different between forest and burn sites (Table 2). Nevertheless,
digestible protein declined over summer at a faster rate in the burn
than in the forest (\emph{t} = 4.75, \emph{p} \textless{} 0.001) (Figure
4). This could be due to the higher initial (June) values of digestible
protein in the burn, as the values for both the burn and the forest were
near or below zero by late summer (August) (Figure 4).

\textbf{Table 2:} Comparison of average digestible protein (kJ/g DM) of
species appearing in both burned and unburned sites in the Alphabet
Hills, Alaska in June, August, and March.\selectlanguage{english}
\begin{longtable}[]{@{}llllllllll@{}}
\toprule
\begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\textbf{Mean (SE)}\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\textbf{Diff}\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\textbf{P-value}\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\textbf{P-value}\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\textbf{Mean (SE)}\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\textbf{Diff}\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\textbf{P-value}\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\textbf{P-value}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\textbf{Alphabet} \textbf{Hills}\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\textbf{Alphabet} \textbf{Hills}\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Burn}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.0614 (0.08)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{June}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.155 (0.053)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Forest}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.059 (0.071)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.0024\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.677\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.677\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{August}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.023 (0.032)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.132\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.132\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{March}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.005 (0.025)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.037\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.037\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textless{}0.0001***\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
S. pulchra\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
S. pulchra\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Burn}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.036 (0.08)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{June}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.14 (0.057)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Forest}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.045 (0.074)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.009\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.009\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.35\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{August}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.014 (0.032)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.126\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.126\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{March}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.017 (0.022)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.031\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.031\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textless{}0.0001***\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
B. nana\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
B. nana\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Burn}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.073 (0.068)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{June}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.148 (0.044)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Forest}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.068 (0.061)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.005\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.66\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.66\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{August}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.037 (0.032)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.111\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.111\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{March}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.018 (0.017)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.019\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.019\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textless{}0.0001***\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
S. glauca\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
S. glauca\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Burn}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.072 (0.087)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{June}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.17 (0.038)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Forest}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.06 (0.083)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.012\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.62\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.62\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{August}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.013 (0.029)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.157\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.157\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{March}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.012 (0.018)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.025\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.025\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textless{}0.0001***\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage} & \begin{minipage}[t]{0.07\columnwidth}\raggedright\strut
\emph{Notes}: DM is dry matter; Diff is the difference between the two
sampling areas, and the two plant genera are \emph{Salix} and
\emph{Betula.} Significant differences were determined with a paired
t-test using a Bonferroni adjustment. Significant differences are
denoted with asterisks. *p\textless{}0.05, **p\textless{}0.01,
***p\textless{}0.0001\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

For winter nutritional quality, digestible energy was significantly
influenced by browse species (F = 6.01, \emph{p} \textless{} 0.0001) and
size class (F = 2.28, \emph{p} = 0.02) but not habitat type (Figure 5).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Figure 5} : Digestible Energy (kJ/ g dry matter) for each
sampled species in the burned and unburned areas. Samples were collected
in March 2018, and are separated by diameter class (cm).

The digestible protein was also significantly influenced by species (F =
25.41, \emph{p} \textless{} 0.0001) and diameter (F = 3.925, \emph{p} =
0.0003) but there was no significant difference between habitat types
(Figure 6). Habitat type did have a significant influence on tannin
content with the burned area having an average of 0.188 mg BSA/g DM (SE
= 0.14) while the forested area had on average 0.23 mg BSA/g DM (SE =
0.14). The negative protein contribution stems from the large
concentration of tannins found in those samples (Figure 6).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\textbf{Figure 6} : Apparent digestible protein (g/g DM) recorded for
each species in the burned and unburned areas. Samples were collected in
March 2018, and are separated by diameter class (cm).

\textbf{Discussion}

We found a significant difference in the canopy cover of the browses
between the burned and unburned area of the Alphabet Hills. Burned sites
had a higher species diversity, which could prove to be more beneficial
to moose if forage diversity lowers the effect of toxins on digestive
function, a hypothesis referred to as the detoxification limitation
hypothesis (Marsh et al. 2006). This hypothesis states that reliance on
a single food source with high amounts of PSMs can limit the overall
detoxification system of an animal (Freeland and Janzen 1974). An
overwhelming amount of PSMs can negatively affect the gut microbiome
which can further limit intake and digestion (Freeland and Janzen 1974,
Dearing et al. 2000, Marsh et al. 2006). Although the forest had higher
canopy cover and higher bite frequency, the overall diversity of the
burn plots may have more of a significant role in the tradeoff between
quantity vs quality of available forage in an area.

Our findings suggest that browse availability in our study site, as
measured by ground cover, was greater in the forest than in the burn,
contrary to the findings of others (Hobbs and Spowart 1984, Blair 1997,
Greene et al. 2012). We attribute this to several potential factors that
could influence the recovery of a site after fire, including the burn
severity, the site conditions prior to the fire, and that many of the
unburned sites were within the total burn perimeter suggesting they were
protected from the fire. The Alphabet Hills area is classified as an
open spruce forest/shrub/bog or as an open and closed spruce forest
(Landhausser and Wein 1993, Crevoisier et al. 2007), which are
characterized by cold, poorly drained organic soils, and overall low
productivity. The forest sites may have been protected from the burn due
to their location of the landscape near more riparian areas or areas
where moisture could accumulate due to the area's topography. Because of
their potential exposure to higher moisture levels as well as retention
trees, or trees that remain alive and standing after a fire (Den Herder
et al. 2009), the browse in forest sites may have had higher
productivity due to reduced stress. The fire history of the area, as
well as the soil characteristics, could explain why there was greater
average canopy cover in the forested sites over the burned sites. The
burn characteristics of the Alphabet Hills fire are more aligned with
the establishment stage of a younger fire which would also explain why
we did not see a significant increase in browse availability in the
burned sites vs the unburned sites.

One potential influence that was not included in this study is the
effect of fire se-verity on nutritional quality and quantity. Intense,
high severity fires could either promote the growth of aspen and other
moose preferred browse due to their ability to bud from their roots, or
they can favor lower quality species that are wind dispersed like birch
(Joly et al. 2016, Wan et al. in press). Although we have relative scale
of severity and how our sampling points align with the fire severity, we
were unable to attribute the variation in plant chemistry to fire
severity. We chose to group plots into burned and unburned to just look
at the two major habitat groupings; this also groups riparian habitats
and habitats with varying sun exposure that were found inside and
outside the burn perimeter. Future work would need to be done to expand
the number and location of sampling sites, as well as adding other
characteristics that indicate changes in severity, such as soil
temperatures at various depths and depth of fuel consumption, to
quantify the effect fire severity has on browse species and therefore
moose.

The significant decrease in digestible energy in the burn over the
forest could be due to a higher desiccation rate in the burn due to the
lack of cover. Shaded plants have been found to have higher levels of
chlorophyll to take advantage of reduced sunlight and thinner cuticle
layers which reduces the amount of indigestible material for a moose (B\selectlanguage{ngerman}ø
and Hjeljord 1991, Gratzer et al. 2004, Hagemeier and Leuschner 2019).
Differences in light availability will also change the distribution of
nutrients and moisture in the soil, further affecting growth and
allocation of resources (Bø and Hjeljord 1991, Gratzer et al. 2004).
Warmer temperatures, both ambient and soil, have been shown to increase
fiber deposition for browse species, lowering the quality for moose (Bø
and Hjeljord 1991, Barboza et al. 2018). For immature plants with
extremely low cell wall concentrations (low structural carbohydrate
concentrations), we may have underestimated DDM and DE. The equations
for digestibility derived in moose by Spalinger et al (2010) were based
on forages of much higher structural carbohydrate concentration, and
plants below approximately 20\% NDF fall outside the domain of those
equations (Robbins et al. 1987, McArt et al. 2006, Spalinger et al.
2010).

Moose are not immobile, although we found that the forested sites had
higher abundance and quality of browse, the moose found within the
Alphabet Hills and the Nelchina basin can move between habitats and in
and out of the area to maintain healthy body condition, promote growth,
and avoid predators. In the summer, females may choose areas that
provide more cover for calving (Oehlers et al. 2011, Joly et al. 2016).
In the winter, after reducing intake rates during the mating season,
males may choose riskier habitat to prevent starvation (Oates et al.
2019). Habitat use is highly dependent on the season, this study chose
to focus on the changes in habitat quality as summer progresses because
that is a critical time for weight gain and growth of new tissues for
males and females (McArt et al. 2009). Because we found an increased
availability of biomass, as well as a higher quality of the browse in
the forest, we may expect that moose in the area will spend a majority
of their time within the forested areas (Searle et al. 2005, 2007).
However, because of the increased diversity of species in the burned
area, it could be a more important habitat for when the plants have the
highest deposition of PSMs. For a moose, the overall dietary value of a
forest stand is transient, often lasting less than 30 years, but moose
need access to a wide age range in forest stands for protection from
predators and available cover for their young (McMahon et al. 2000, Osko
et al. 2004, Dussault et al. 2006, Joly et al. 2016). Further work is
necessary to link movement of individuals throughout the area to the
nutritional quality and bite frequencies throughout the year in this
fire as well as other fires across the state.

Although others have shown a positive effect of wildfire for herbivore
populations, we found that some areas, including the Alphabet Hills
area, may not be suitably adapted to benefit from the quick release of
nutrients after fire and may not allocate more resources to biomass as
previously expected (Hobbs and Spowart 1984, Rea and Gillingham 2001).
These findings highlight the importance of quantifying both availability
and quality of food resources for herbivores, when addressing the
benefits of fire. We showed that a traditional method of increasing
available habitat for moose is not applicable for all habitats or areas.
In the future, habitat management strategies that include wildfire
should consider the history of the area and the pre-fire communities, as
well as how fire can shift resource availability. Field surveys of
pre-fire community characteristics such as understory community
composition and individual species densities with paired surveys of
plant chemistry is necessary to ensure that the fire is increasing
biomass reachable by moose, while also increasing the nutritional
quality. Soil characteristics, such as its water retention capacity and
microbial community can also have a significant effect on post fire
vegetation communities and their nutritional quality after wildfire and
should be assessed before prescribing fires for habitat enhancement.
Although logistically challenging, predictions of how fires may affect
wildlife should be based on assessments of previously burned stands
having similar physical and biological characteristics.

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