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\begin{document}

\title{Temporal and spatial dynamics of small terrestrial mammals inhabiting a
degradation gradient in a lowland tropical forest in Uganda}



\author[1]{Sadic Babyesiza}%
\author[2]{Georgies Mgode}%
\author[3]{Joseph Mpagi}%
\author[2]{Christopher Sabuni}%
\author[3]{James Ssuuna}%
\author[2]{Sisiria Akoth}%
\author[2]{Abdul Katakweba}%
\affil[1]{Makerere University}%
\affil[2]{Sokoine University of Agriculture}%
\affil[3]{Busitema University}%


\vspace{-1em}



  
  \date{May 28, 2024}


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\selectlanguage{english}
\begin{abstract}
A study aimed at assessing the structure of rodent and shrew assemblages
inhabiting a degradation gradient while considering rainfall patterns,
was conducted in one of few remaining lowland tropical forests in
Eastern Africa. We collected a unique dataset of rodents and shrews,
representing 24 species (19 rodents, 5 shrews). The most abundant
species alternated in dominance as species abundance significantly
fluctuated across the study period following a degradation gradient
(F2,33 = 5.68, p = 0.007). While only generalist species were observed
near the degraded forest edge, habitat specialists such as Deomys
ferrugineus, Malacomys longipes and Scutisorex congicus, were observed
in the primary forest interior suggesting a significant (X2 = 1165.329,
P\textless{}0.001) association between species and their associated
habitats and habitat attributes. There was also an observed correlation
between rainfall patterns and species abundance. Capturing more species
in adjacent fallows and along the degraded forest edge suggests that
many species are able to live in degraded habitats that offer a variety
of food resources. The continued pressure on forest resources, however,
may lead to changes in habitat structure. This, coupled with the
dependence of forest ecological functions on rainfall, which is
typically not the case, may ultimately cause the local extinction of
highly specialized but less adaptable species.%
\end{abstract}%



\sloppy


\textbf{Abstract}

A study aimed at assessing the structure of rodent and shrew assemblages
inhabiting a degradation gradient while considering rainfall patterns,
was conducted in one of few remaining lowland tropical forests in
Eastern Africa. We collected a unique dataset of rodents and shrews,
representing 24 species (19 rodents, 5 shrews). The most abundant
species alternated in dominance as species abundance significantly
fluctuated across the study period following a degradation gradient
(F\textsubscript{2,33} = 5.68, p = 0.007). While only generalist species
were observed near the degraded forest edge, habitat specialists such
as\emph{Deomys ferrugineus, Malacomys longipes} and \emph{Scutisorex
congicus} , were observed in the primary forest interior suggesting a
significant (X\textsuperscript{2} = 1165.329, P\textless{}0.001)
association between species and their associated habitats and habitat
attributes. There was also an observed correlation between rainfall
patterns and species abundance. Capturing more species in adjacent
fallows and along the degraded forest edge suggests that many species
are able to live in degraded habitats that offer a variety of food
resources. The continued pressure on forest resources, however, may lead
to changes in habitat structure. This, coupled with the dependence of
forest ecological functions on rainfall, which is typically not the
case, may ultimately cause the local extinction of highly specialized
but less adaptable species.

\textbf{Key words:} Habitat degradation, Rainfall patterns, Habitat
association, Rodents, Shrews

\subsection*{1.0 INTRODUCTION}

{\label{introduction}}

Deforestation in Uganda has been severe over the years due to the
continued dependence on natural resources for food, energy, medicine and
the growing human settlements close to protected areas. Forests in
Uganda have been severely degraded and their diversity compromised. Obua
et al. (2010) noted an estimated loss of 86\% of Uganda's tropical moist
forest especially on private land, while National Forestry Authority
reported an 88\% and 2 \% loss of tropical well stocked forest on
private land and protected areas, respectively, between 1990 and 2015
(NFA 2016). This is mainly as a result of the increasing human
population that has overtime encroached on forested areas for both
settlement and farming (Mulugo et al. 2019).

Few countries of equivalent size have as rich and diverse rodent and
shrew fauna as Uganda. Apart from many species of rats and mice there is
a great variety of other forms including gerbils, squirrels, flying
squirrels, porcupines, cane rats, mole rats, and dormice (Delany 1975).
The main factors causing this high diversity are the geographical
position at the margin of several major biogeographical areas (Linder et
al. 2012) and the wide range of altitudes and the complex array of
vegetation which support a characteristic rodent fauna (Delany 1975).

A variety of micro habitats with varying characteristics can be found in
tropical forests, and rodents and shrews are two of the most
species-rich groups of mammals that live there (Carleton \& Musser
2005). Because of their diversity and abundance, they are some of the
most significant players in the ecological dynamics of forest ecosystems
(Angelici \& Luiselli 2005). They are essential to the transport of
nutrients and materials through the ecosystem and to the food web
(Nicolas et al. 2009). In disturbed ecosystems, rodents play important
roles in succession as seed dispersers (Nicolas et al. 2009). In
contrast, shrews prey on insects and smaller vertebrates (Nicolas et al.
2009) and the population dynamics of their prey are regulated by their
voracious feeding habits. Shrews and rodents are both eaten by larger
vertebrates like birds and snakes. They are economically important as
crop pests and medically important, with many zoonotic heamoparasites
such as borrelia, trypanosomes, bacilli, plasmodia and coccobacilli
(Katakweba et al. 2012), and can also be employed in ecological
evaluation for conservation decision-making.

One of the elements that shapes and influences small mammal groups in
tropical forests is habitat structure (Tews et al. 2004). In a Brazilian
rain forest, Pardini et al. (2005) discovered that the forest structure
affected both the overall abundance of species and the abundance of
particular species on an individual basis. In Africa, where the majority
of these natural areas are threatened by anthropogenic activities, there
has generally been a dearth of ecological study on rodents and shrews in
all habitats (Nicolas et al. 2009, Obua et al. 2010). Even though there
is a lot of forest damage in Africa, these activities' immediate and
long-term repercussions are rarely examined (Malcom \& Ray 2000). Few
studies have specifically looked at how habitat degradation affects
small mammal groups over time in Africa (e.g. Struhsaker 1997, Malcolm
\& Ray 2000). Small mammal communities' reactions, whether individual or
collective, provide evidence of the effects of disruptions. Some of the
most significant human-mediated disruptions to forest ecosystems are
expanding agriculture, selective harvesting for lumber, and charcoal
burning, among others (Malcolm \& Ray 2000, Baranga 2007, Obua et al.
2010). Depending on the extent, severity, and kind of the disturbance,
as well as the context of the landscape, human-induced habitat
alterations have both direct and indirect consequences on small mammal
groups (Malcolm \& Ray 2000).

A number of surveys of rodents and shrews of Uganda Forest Reserves have
been previously conducted. Basuta and Kasenene (1987) reported 14
species from a study in Kibale Forest National Park, Davenport et al.
(1996) and Howard et al. (1996) reported on more comprehensive small
mammal surveys from Ugandan forests. In the Mabira Central Forest
Reserve (CFR), Dickinson \& Kityo (1996) conducted earlier surveys of
the rodent and shrew population, followed by the recent survey conducted
by Waswa et al. (2016) and Ssuuna et al. (2020). These studies assessed
small mammals throughout the forest with a variety of objectives;
Dickinson \& Kityo (1996) focused on the distribution of species,
whereas Waswa et al\emph{.} (2016) examined the composition and
organization of rodent communities and Ssuuna et al\emph{.} (2020)
assessed rodent communities in different forest compartments with
varying degrees of degradation. However none of these studies has looked
at spatial and temporal dynamics of rodent and shrew communities in MCFR
along a degradation gradient while considering habitat characteristics
and rainfall patterns.

Mabira CFR is uniquely located between metropolitans of Lugazi, Mukono,
Jinja, and Kampala city (Fig. 1). As a result, the forest is under a lot
of pressure to provide a variety of products, the most important of
which are charcoal and timber. The forest is currently being invaded by
the invasive paper mulberry, which has taken over all of the forest
boundaries as gaps have opened up. Numerous groups of rodents and shrews
that depend on forests, particularly highly specialized ones with low
degrees of adaptation, may be pushed toward local extinction as the size
of natural habitats declines. The situation is made worse by the general
lack of studies, species monitoring programs, and/or habitat monitoring
programs in the region, which causes biodiversity to decline in the
absence of a baseline.

A thorough grasp of rodents and shrew ecological niches is necessary to
properly explain their importance to the dynamics of the forest
ecosystem. Such data is required to classify specific forest sections'
management regimes and/or forest habitats according to how important
they are to the local wildlife. It is hoped that the study highlights
the effect of forest habitat deterioration on a micro scale hence
stimulate fresh approaches for management of MCFR and other forests in
Uganda. Mainly the study focuses on temporal and spatial changes in
assemblages of rodents and shrews living along a degradation gradient.
The main specific objectives are: (i) to assess the diversity and
distribution of rodents and shrews along a habitat degradation gradient;
(ii) to evaluate how habitat characteristics affect the occurrence of
rodents and shrews along a habitat degradation gradient; (iii) to
analyse how rainfall patterns affect the abundance of rodents and shrews
along a degradation gradient.

\subsection*{2.0 METHODS}

{\label{methods}}

\subsection*{2.1 Study areas}

{\label{study-areas}}

The study was conducted in Mabira (CFR); (Fig. 1) in Uganda Griffin
Falls (0\selectlanguage{ngerman}°26'14.28''N, 32°57'14.31''E, 1179 m a.s.l.) from August
2018-December 2019. This is the largest forest reserve in Central Uganda
(Colwell \& Coddington 1994), managed by Uganda National Forestry
Authority (NFA) as a Central Forest Reserve (CFR). According to Howard
(1991) MCFR is considered secondary regenerating, in which the most
dominant vegetation represents sub culmination communities, heavily
influenced by man through continued excess of illegal resource use and
encroachment. However, some parts are now fully regenerated with tall
mature trees especially in the strict nature reserve compartment of the
forest (Ministry of water and environment 2010). The MCFR's vegetation
is classified as a semi-deciduous medium altitude forest. Mabira forest
continues to exist in central Uganda as an isolated but sizable forest
island without any land linkages to the various little pockets of forest
in the Lake Victoria basin. Mabira (CFR) has a special position as the
last substantial sanctuary for forest biota in this area due to its
survival as the only fairly large contiguous forest estate in this area
(Kityo 2008).

\subsubsection*{2.2 Study design}

{\label{study-design}}

The study was conducted in the village of Namusa in the MCFR for 12
months between August 2018 and December 2019. Data were intermittently
collected (with a one-month break after two months of data collection)
along a gradient of habitat degradation that included a primary forest
interior, a degraded forest edge, and fallows, gardens, sugarcane
plantations, homesteads close to the forest, collectively referred to as
adjacent habitats (Figure 1). For every sampling regime, nine transects
were set in subjectively selected sites, namely primary forest interior,
depleted forest edges and adjacent habitats (Figure 1). Rodents and
shrews were trapped using Sherman traps set in transects of 200 m with
20 stations and an inter-station distance of 10 m with a trapping effort
of 40 traps per transect (Mulungu et al. 2011). Traps were baited with a
mixture of peanut butter, maize flour, ripe bananas and silver fish, and
traps laid out for 3 nights. Morphometric measurements were taken from
every captured specimen including the total length (TL), tail vertebrae
length (TV), hind foot length (Hf), ear length, and weight (Wt). All
measurements were recorded in millimeters and weight in grams. All
specimens collected were kept as wet specimens in 75\% ethanol and kept
as vouchers in Makerere zoological museum. Collected specimens were
identified to species using morphometric measurements cross references
with published identification guides (Brambell 1973, Delany 1975, Thorn
\& Kerbis 2009, Monadjem et al. 2015) For selected individuals of each
morphotype, identifications were confirmed by sequencing of partial
mitochondrial cytochrome b gene (i.e. DNA barcoding) from 96\%
ethanol-preserved samples at the Institute of Vertebrate Biology (IVB)
of the Czech Academy of Sciences. Obtained sequences were compared with
the sequences in GenBank and further unpublished sequences in the
database of IVB. The barcoding protocol (i.e. used primers, PCR
conditions and sequencing) is described in Bryja et al. (2014).
Microhabitat variables were also subjectively recorded by observation
for every transect. These were canopy cover (Delineated by percentage
cover where any cover below 40\% was considered as no canopy cover),
forest undergrowth (measured by low, medium, max), while water source
(with aa 500m proximity) and leaf litter (which was measured by presence
or absence). Vegetation cover type (garden, fallow and plantation) was
used for adjacent habitats. Average monthly rainfall data was obtained
from the Sugar Cooperation of Uganda Lugazi (SCOUL) and used to assess
how species abundance fluctuates with rainfall over time

\subsubsection*{2.3 Data analysis}

{\label{data-analysis}}

Trapping success (TS) was computed using the formula;

\begin{equation}
TS=\left(\frac{N_{i}}{T_{n}}\right)\times 100\nonumber \\
 \end{equation}

Where; \(N_{i}=\) number of specimens
collected\(,T_{n}=total\ number\ of\ traps\ se\)t.

Shannon-Wiener diversity index was computed from the formula;

H'=-pi [?] ln pi

where

pi is the proportion of individuals found in species i

ln Natural logarithm

Species abundance was assessed based on the number of individuals
recorded for every species.

Correspondence analysis (CA) was performed for the different sampling
sites to show the chi-square distance among sites and also assess the
significance of association between species and habitats.

To certify adequate sample size, rarefaction curves were developed using
Vegan statistical package in R (Oksanen et al. 2016). Where the smoothed
averages of the individual curves represent the statistical expectation
of species accumulation per sampling site.

Small mammal community composition and association was measured using
``multipatt'' function in ``R'' using packages ``vegan'' and
``indicspecies'' (Miquel De Caceres 2013). In order to run an indicator
species analysis, a vector containing the classification of the sites
micro habitat types into groups was done using non-hierarchical cluster
analysis with different ``r'' functions in packages ``indicspecies'' and
``vegan''. In order to determine which species can be used as indicators
of different sampling sites; an approach commonly used in ecology is the
use of the Indicator Value index (Dufr\^{}ene \& Legendre 1997, De
Caceres et al. 2010). The approach calculates the ``IndVal'' (indicator
value) index between the species and each site group and then looks for
the group corresponding to the highest association value, the
statistical significance of this relationship is then tested using a
permutation test. All analyses were performed with R statistical
software R Core Team (2013). Multiple linear regression was carried out
to assess the relationship between species richness and species
abundance with rainfall. The assumption is that species richness and
abundance follow rainfall patterns. Line graphs were made to examine for
any temporal trends in species richness and abundance, while cross
correlation graphs were made to seek for relationship patterns between
species richness, abundance and rainfall.

\textbf{3.0 RESULTS}

\textbf{3.1 Species composition and abundance}

A total of 1411 individuals were captured from 18360 trap nights
representing 19 species of murid rodents (Muridae) and 5 species of
shrews (Soricidae) (Table 1). Species richness was equally highest in
adjacent habitats and degraded forest edges with 19 species, and lowest
in primary forest interior. Species diversity was highest in adjacent
habitats and least in the primary forest interior while trap success was
highest in adjacent habitats and least along the degraded forest edges
(Table 1).

\emph{Hylomyscus stella} and \emph{Praomys jacksoni} were the most
abundant species in forested areas while \emph{Lemniscomys striatus} was
the most abundant in adjacent habitats (Table 1). \emph{Lophuromys
stanleyi and Crocidura olivieri} were the only species recorded from all
sampled habitats. Other notable species recorded include\emph{Scutisorex
congicus} (Hero shrew), \emph{Deomys ferrugineus} and\emph{Malacomys
longipes} , i.e. typical Congo basin forest species with MCFR being
their eastern geographical limit (Thorn \& Kerbis 2009, Monadjem et al.
2015, IUCN 2018).

\textbf{3.2. Species accumulation}

A comparison of species accumulation in relation to sample size using
rarefaction curves shows that adjacent habitat areas attained the
asymptote while curves of degraded forest edges and primary forest
interior did not attain the asymptote (Fig. 2). For the sites that did
not attain the asymptote it means that further surveys might yield more
species.

\subsubsection*{3.3. Rodent and shrew habitat association in Mabira
Central Forest
Reserve}

{\label{rodent-and-shrew-habitat-association-in-mabira-central-forest-reserve}}

The different microhabitat attributes for the different survey areas in
MCFR were clustered forming groups as a result of association of
different species with different habitat attributes. \emph{Group 1} is
associated with closed canopy habitats, \emph{Group 2} is associated
with grass fallow, gardens, bush fallow and sugarcane
plantations,\emph{Group 3} is associated with thick undergrowth and leaf
litter;\emph{Group 4} is associated with habitats around homes; and
\emph{Group 5} had habitats associated with rivers, streams and open
canopy.

An indicator species analysis was completed, and an indicator species
list for each microhabitat (or microhabitat group combination) was
obtained. Two species \emph{Scutisorex congicus} and \emph{Praomys
missonnei} were found to be significantly associated (p=0.043 and 0.051
respectively) with closed canopy, leaf litter and thick
undergrowth.\emph{Mastomys erythroleucus} was significantly associated
with grass and bush fallows, gardens and plantations (p=0.012).
\emph{Cricetomys ansorgei} , \emph{Hylomyscus stella} and \emph{Praomys
jacksoni} , were associated with microhabitat groups one, three and five
at p=0.012, p=0.025 and p=0.026 respectively.

The chi square test of independence between the different habitat
variables and species (X\textsuperscript{2} = 1165.329, P=0.000001),
suggests that there is a significant strong association between species
and their associated habitats. A correspondence analysis graph showing
the chi-square distances among sites of MCFR and the strength of
association between species and sampling areas is represented in Figure
3.

\textbf{3.4 Temporal fluctuations in rodent and shrew abundance in
Mabira (CFR)}

Overall abundance of small mammals significantly varied across habitats
(F\textsubscript{2,33} = 5.68, p = 0.007). Adjacent habitats were
characterized by the highest abundance (mean = 44.33\selectlanguage{ngerman}±12.6), followed by
primary forest interior (mean = 36.4±13.4) and the least abundance along
degraded forest edges (mean = 27.4±10.8). Temporal fluctuations in
abundance for four most abundant species indicates peaks
for\emph{Hylomyscus stella} in September, December and May with least
captures in March, \emph{Praomys jacksoni} had peaks in
September-November, February and May with least captures in December
while \emph{Hylomyscus stella} was at a peak (Figure 4). In adjacent
forest habitats, \emph{Lemniscomys striatus} had two peaks in September
and March while \emph{L. stanleyi} showed two major peaks in December
and March (Figure 4). It was also observed that species sharing the same
habitat alternate in dominance over time

\textbf{3.5 Effect of rainfall on species abundance along a degradation
gradient}

A linear regression analysis revealed that species abundance was not
significantly influenced by rain with an R\textsuperscript{2}~= 0.003.
However, cross correlation graphs for species abundance and rainfall
along the degradation gradient revealed some relationships and patterns,
with species abundance in adjacent habitats and degraded forest edge
showing a strong correlation with rainfall. While in primary forest
interior the correlation was weak (Fig 5). Further analyses to assess
how the most abundant species in the forest and adjacent habitats
fluctuate with rainfall revealed that forest species abundance is not
influenced by rain as compared to those outside the forest (Fig 6).

\textbf{4.0 DISCUSSION}

\textbf{4.1 Diversity and spatial variations of rodents and shrews}

The overall rodent and shrew species composition inhabiting the forest
ecosystems of Mabira Central Forest Reserve is relatively diverse as
reflected in the high number of determined species (20 rodents and 5
shrews). Previous studies have also recorded high species numbers. For
example, Ssuuna et al\emph{.} (2020) reported 14 rodent species, Kasozi
(2017) reported 11 rodents and five shrews, Waswa et al\emph{.} (2016)
reported 13 rodents and seven shrews, while Dickson \& Kityo (1996)
reported 13 rodents and 2 shrews. This could be attributed to the fact
that MCFR represents the only contiguous large mass of forested habitat
acting as refugia for many forest dependent species (Kityo 2008, MWE
2017). The rarefaction curves for the four sampling areas in MCFR (Fig.
2) suggest that the techniques used were effective for sampling the
rodent and shrew communities but more sampling effort is still required
in forested areas because of the fewer shrew species collected compared
to those in Waswa et al\emph{.} (2016) who additionally reported
a\emph{Crocidura} novice. This could be because we did not employ
pitfall traps, which are a more effective method of trapping shrews
(Umetsu et al. 2006, Stromgren \& Sullivan 2014).

The primary forest interior has some habitat specialists such
as\emph{Malacomys longipes} which was collected mostly along the river
(Kerbis \& Patterson 1995) and \emph{Deomys ferrugineus,} while along
the degraded forest edge only adaptive habitat generalist species such
as \emph{P. jacksoni} and \emph{L. stanleyi} were recorded\emph{. L.
stanleyi} , although considered an Albertine rift endemic (Monadjem et
al. 2015) it is believed to be widely occurring over arrange of habitats
(Monadjem et al. 2015). Pardini et al. (2005), Lucie \& Séverine (2016)
reported that specialized species of rodents and shrews disappear
following primary forest disturbance. The fact that more species have
been recorded in adjacent fallows and along the degraded forest edge
suggests that, many species are adapting or prefer to living in
disturbed habitats Lucie \& Séverine (2016). Any form of disturbance in
a forest opens up space giving rise to various plants that were
previously surpassed by low light (Catford et al. 2012) which in turn
provide more food alternatives. This abundance of herbaceous plants
provides cover and food for various species hence increase in diversity
(Brockerhoff et al. 2017). However, the plight of specialized species is
in balance with chances of being out-competed by the more aggressive
species and ultimately eliminated from their habitat (Thomas et al.
2013\textbf{)} . The continuing illegal activities of resource
extraction in MCFR (MWE 2016) continue to reduce the habitat quality for
rodents and shrews in the reserve. The recording of new records for the
forest is not in its self a testament of the quality of habitat but
rather a fact that the forest is understudied. The continued decline in
habitat quality in Mabira CFR and its surrounding, is reflected in the
lack of records of grassland specialists like \emph{Mylomys dybowskyi
and Lemniscomys zebra} (as \emph{barbarus} ) recorded in Davenport et
al. (1996) but have not been reported in the preceding surveys. Habitat
quality is compromised through loss of canopy cover, reduction in
decaying logs since many are extracted as firewood, and reduction in
plant species richness through logging which gives chance to the evasive
paper mulberry to proliferate (Mulugo et al. 2019), this in time will
lead to loss of rodent and shrew species forest specialists (Lucie \&
Séverine 2016, Pardini et al. 2005).

\textbf{4.2. Effects of vegetation cover characteristics on the
occurrence of rodents and shrews}

Vegetation cover is a major driver in the occurrence and distribution of
various rodent and shrew species Flores-Peredo and Va\selectlanguage{english}zquez-Domi\selectlanguage{english}nguez
(2016), various vegetation assemblages such as forest, fallow, garden,
and plantations as exploited in this study provide varying degrees of
food resources and cover. As such most species have co-evolved to occupy
various vegetation assemblages given the resources available (Avenant
2011). Even the more adaptive such as \emph{Mastomys erythroleucus} can
only occur in a select group of habitats (section 3.2) but not
everywhere. The observed association between species and type of site,
suggests that different species have different habitat requirements.
Therefore, the more diverse an ecosystem is in terms of habitat
characteristics, consequently making it have a high microhabitat
diversity and an equally high species diversity Bantihun \& Bekele
(2015). As noted by Johnson \& Horn (2008), the distribution of species
is dependent on habitat type, vegetation cover, and microhabitat
characteristics. For example, \emph{Scutisorex somereni} was
significantly associated with forested environs of closed canopy and
leaf litter. This is in line with findings of Kasozi (2017), who stated
that it was associated with primary forest with leaf litter. Such
findings also help emphasize the importance of some habitats and their
attributes as key to species conservation Lucie \& S\selectlanguage{ngerman}éverine (2016). With
the facts above its important to protect the forest with all its
microhabitat diversity by regulating illegal and high resource
extraction.

\textbf{4.3. Rainfall as a driver of temporal fluctuations of rodent and
shrew species abundance along a degradation gradient}

The observed rodent and shrew species fluctuation, is indicative that
rodent species abundance follows seasonal busts in food which also
follows rainfall patterns. Mesele \& Bekele (2012) noted that
fluctuations in species abundance is a result of~seasonal variation~in
vegetation structure, ground cover and other related environmental
variables which are also driven by rainfall patterns. Alternation in
abundance of species occupying the same habitat (Figure 4) could be as a
result of resource partitioning mainly through dietary separation of
species with similar requirements (Symes et al. 2013).

Rainfall is a known factor that drives rodent and shrew demography in
various ecosystems (Thomas \& Richard 1999, Delany 2008, Pavey \& Nano
2013), however in this study, fluctuations in species abundance in
forested environments, did not correlate to fluctuations in rainfall as
compared to habitats outside forest. This is because forest ecosystems
create a micro climate usually independent of the overall climate of an
area (Pieter et al\emph{.} 2021). Comparisons of abundant species in
forest and adjacent habitats revealed similar trends suggesting that
fluctuations in abundance of forest species may not be explained by
weather patterns alone but maybe a combination of both biotic and
abiotic factors (Ward-Fear et al. 2021). With the degradation and
microhabitat modification, forest resident species population will be
forced to follow fluctuations in weather variables calling for
adaptations. Species that cannot quickly adapt will most likely be
eliminated from the ecosystem leading to local extinctions.
(Ocampo-Peñuela et al. 2020).

\textbf{5.0 CONCLUSION and RECCOMENDATION}

Mabira (CFR) is an important forest for rodent and shrew species
conservation and ecological research given the high species diversity
and high density. The recording of \emph{Hylomyscus stella}
and\emph{Praomys jacksoni} in high numbers can be used as a proxy to
monitor the health of the forest, this can be done in combination with
the forest specialist species like \emph{Deomys ferrugineus}
,\emph{Praomys missonei} and \emph{Malacomys longipes}
recorded\emph{.}Some species were observed to be associated with certain
habitats, suggesting that they have different habitat requirements and
highlighting the importance of habitat heterogeneity. This also provides
useful information required for habitat management like protecting the
forest from any activities leading to habitat modification. Rodent and
shrew species abundance fluctuations are independent of the local
rainfall patterns but with the ongoing habitat modification, forest
mammals may have to adapt to changes in the rainfall patterns which
patterns are increasingly becoming unpredictable. This implies that
species that will not be able to adapt fast might be ultimately
eliminated from the ecosystem. From this study, we recommend an
assessment of how habitat homogeneity due to the proliferation
of\emph{Broussonetia papyrifera} , which is invading the forest
following forest degradation, affects rodent and shrew populations in
forested environments.

\textbf{6.0 REFERENCES}

\selectlanguage{polish}\textbf{Aghová, T., Šumbera, R., Piálek, L., Mikula, et al. (2017)}\selectlanguage{ngerman} .
Multilocus phylogeny of east African gerbils
(Rodentia,\emph{Gerbilliscus} ) illuminates the history of the
Somali-Masai savanna. J Biogeogr. 2017;44:2295--307.

\textbf{Angelici, F. M. and Luiselli, L., (2005)} . Patterns of speci\selectlanguage{english}fic
diversity and population size in small mammals from arboreal and
ground-dwelling guilds of a forest area in southern Nigeria. \emph{J.
Zool., Lond} . 265: 9--16.

\textbf{Avenant, N. (2011).} The potential utility of rodents and other
small mammals of indicators of ecosystem integrity of South African
grasslands. \emph{South African Journal of Wildlife
Research}38:626--639.

\textbf{Baranga, D., (2007)} . Observations on resource use in Mabira
Forest Reserve, Uganda. African Journal of Ecology, \emph{Afr. J. Ecol}
. 45 (Suppl. 1): 2--6.

\textbf{Bantihun, G., and Bekele, A. (2015).} Diversity and habitat
association of small mammals in Aridtsy forest, Awi Zone,
Ethiopia.~\emph{Dong wuxueyanjiu = Zoological research} ,~\emph{36} (2),
88--94. https://doi.org/10.13918/j.issn.2095-8137.2015.2.88

\textbf{Brambell, M. (1973).} The Mammals of Africa---an Identification
Manual, edited by J. Meester and H. W. Setzer. Smithsonian Institution
Press, Washington.

\textbf{Brockerhoff, E.G., Barbaro, L., Castagneyrol, B.~et al.(2017).}
~Forest biodiversity, ecosystem functioning and the provision of
ecosystem services.~\emph{Biodivers Conserv} ~\textbf{26} , 3005--3035.
https://doi.org/10.1007/s10531-017-1453-2.

\selectlanguage{polish}\textbf{Bryja, J., Mikula, O., Šumbera, R, Meheretu, Y., Aghova,
T.,~Lavrenchenko, L., Mazoch\emph{,} V., Oguge, N., Mbau, S.J.,
Welegerima, K., Amundala, N., Colyn, M., Leirs, H and Verheyen, E
(2014).}\selectlanguage{english} Pan-African phylogeny of~\emph{Mus} ~(subgenus~\emph{Nannomys}
) reveals one of the most successful mammal radiations in
Africa.~\emph{BMC Evol Biol} ~\textbf{14} , 256 (2014).
https://doi.org/10.1186/s12862-014-0256-2

\textbf{Catford, J.A., Daehler, C.C., Murphy, H.T, et al. (2012).} The
intermediate disturbance hypothesis and plant invasions: Implications
for species richness and management''.~Perspectives in Plant Ecology,
Evolution and Systematics.~14~(3): 231--
41.~doi:10.1016/j.ppees.2011.12.002

\textbf{Colwell, R.K. and Coddington, J.A. (1994).} Estimating
terrestrial biodiversity through extrapolation. Phil. Trans. R. Soc.
Lond. B 345: 101-118.

\textbf{Delany, M. (2008).} Ecology of small rodents in Africa. Mammal
Review. 16. 1 - 41. 10.1111/j.1365-2907.1986.tb00016.x.

\textbf{Delany, M. (1975).} The Rodents of Uganda.764, ISBN
0565007645.Kettering Northamptonshire.

\textbf{Dickinson, C. and Kityo, R. (1996)} Small mammals. In:
Davenport, T., Howard, P. and Baltzer, M. (eds). \emph{Mabira Forest
Reserve Biodiversity Report} . Forest Department, Kampala, Uganda.

\textbf{Dufr\^{}ene, M \& Legendre, P (1997).} Species assemblages and
indicator species: the need for a flexible asymmetrical approach.
Ecological Mono-graphs, 67(3):345\{366.

\textbf{Flores-Peredo, R and Vazquez-Dominguez, G (2016).}\selectlanguage{english} Influence of
vegetation type and season on rodent assemblage in a Mexican temperate
forest mosaic. \emph{Therya, 2016, vol. 7 (3): 357-369}

\textbf{Howard, P.C. (1991).} Nature Conservation in Uganda's Tropical
Forest Reserves.313pp. IUCN, Gland, Switzerland and Cambridge, UK.

\textbf{Johnson, M.D. and C.M. Horn, (2008).} ~Effects of rotational
grazing on rodents and raptors in a Coastal Grassland. Western N. Amer.
Nat., 68: 444-452.

\textbf{Kerbis Peterhans, J. C. \& Patterson, B. D. (1995).} The
Ethiopian water mouse \emph{Nilopegamys} Osgood, with comments on
semi-aquatic adaptations in the African Muridae. \emph{Zoological
Journal of the Linnean Society} 113: 329-349

\textbf{Kasozi, H (2016).} Relation of small mammal communities to
habitat with observations on the ranging patterns of the hero shrew
(\emph{scutisorexsomereni} ) in Mabira CFR. \emph{Un published Msc
Thesis Makerere University}

\textbf{Kityo, R, M. (2008).} Bat communities in some disjunct areas of
central and western Uganda: implications for their conservation. PHD
thesis Makerere University.

\selectlanguage{ngerman}\textbf{Lucie, B and Séverine, V. (2016).} Ecological strategies in
stable and disturbed environments depend on species
specialization.\emph{OIKOS synthesizing ecology,} Volume 125- Issue-10,
Pages 1408-1420

\textbf{Malcolm, J. R. and Ray, J. C., (2000)} . Influence of Timber
Extraction Routes on Central African Small Mammal Communities, Forest
Structure and Tree Diversity. \emph{Conservation Biology} 14 (6):
1623-1638.

\textbf{Ministry of Water and Environment (2010).} Forest Management
plan for Mabira Central Forest Reserves (Mabira, Nadagi, Namakupa,
Namawanyi/Namananga \& Kalagala Falls Central Forest Reserves) for the
period 1st July 2009-30th June 2019, Ministry of Water and Environment,
Kampala

\textbf{Miquel De Caceres (2013).} How to use the indicspecies package
(ver.1.7.1), Centre Tecnol\_ogicForestal de Catalunya. Ctra. St.
Lloren\_cdeMorunys km 2, 25280, Solsona, Catalonia, Spain.

\textbf{Monadjem, A., Taylor., Christiane Denys, et al. (2015).} Rodents
of Sub-Saharan Africa, a

biogeographic and taxonomic synthesis. PI books GmbH, Leck. e-ISBN (PDF)
978-3-11- 030191-5.© 2015 Walter de Gruyter GmbH, Berlin/Munich/Boston.

\textbf{Mulugo, L.W., Galabuzi, C., Nabanoga, G.N.,~et al. (2019).}
~Cultural knowledge of forests and allied tree system management around
Mabira Forest Reserve, Uganda.~\emph{J. For.
Res.}https://doi.org/10.1007/s11676-019-00961-6

\textbf{Mulungu, L. S., Massawe, A. W., Kennis, et al.
(2011).}Differences in diet between two rodent species , Mastomys
natalensis and Gerbilliscus vicinus , in fallow land habitats in central
Tanzania \selectlanguage{english}+.\emph{African Zoology} , \emph{46} (October 2011), 387--392.

\textbf{Musser, G. G. \& Carleton, M. D. (1993).} Family Muridae. InD.
E. Wilson \& D. M. Reeder (Eds) Mammal Species of the World: A Taxonomic
and Geographic Reference, 2nd edn (pp.501--755). Washington and London:
Smithsonian Institution Press.\textbf{National forestry Authority
(2016).} State of Uganda's forests as of 2015, Ministry of water and
environment. https://www.nfa.org.ug/images/reports/forestryreport.pdf

\textbf{Nicolas, V., Barrie`re, P., Tapiero, A, et al. (2009)} . Shrew
species diversity and abundance in Ziama Biosphere Reserve, Guinea:
comparison among primary forest, degraded forest and restoration
plots.\emph{Biodivers Conserv} . (18): 2043--2061.

\textbf{Obua, J., Agea, J.G and Ogwal, J.J (2010).} ``Status of Forests
in Uganda Review Article Status of Forests in Uganda.'' \emph{African
Journal of Ecology} , no. February:0--7. https://doi.org/10.1111/j.1365-
2028.2010.01217.x

\textbf{Ocampo-Penuela, N., Garcia-Ulloa, J., Kornecki, I, et al.
(2020).} Impacts of Four Decades of Forest Loss on Vertebrate Functional
Habitat on Borneo. Front. For. Glob. Change 3:53. doi:
10.3389/ffgc.2020.00053.

\textbf{Oksanen, J., Blanchet, F.G., Kindt, R, et al. (2016)} . vegan
Community Ecology Package Version 2.3-3. URL https://cran.r-
project.org/web/packages/vegan/.

\textbf{Pardini, R., Marques de Souza, S., Brag-Neto, R, et al.
(2005).}The role of forest structure, fragment size and corridors in
maintaining small mammal abundance and diversity in an Atlantic forest
landscape.\emph{Biological Conservation} , \textbf{124} :253-266.

\textbf{Pavey, C and Nano, C.E.M. (2013).} Changes in richness and
abundance of rodents and native predators in response to extreme
rainfall in arid Australia. Australa Ecology. 38. 777-785.
10.1111/aec.12062.

\textbf{Pieter, F., Jonathan, L., Miska, L, et al. (2021).} Forest
microclimates and climate change: Importance, drivers and future
research agenda. 27. 10.1111/gcb.15569.

\textbf{Stromgren, E.J., and Sullivan, T.P. (2014).} Influence of
pitfall versus Longworth livetraps, bait addition, and drift fences on
trap success and mortality of shrews.~\emph{Acta Theriol} ~\textbf{59,~}
203--

\textbf{Struhsaker, T. T., (1997)} \emph{. Ecology of an African Rain
Forest: logging in Kibale and the conflict between conservation and
Exploitation} . University Press of Florida, Gainesville.

210 (2014). https://doi.org/10.1007/s13364-013-0149-6

\textbf{Symes C, Wilson J, Woodborne S, et al. (2013),} Resource
partitioning of sympatric small mammals in an African forest-grassland
vegetation mosaic. Voi -- 38, \emph{Austral Ecology} . Doi -
10.1111/aec.12020

\textbf{Ssuuna, J., Makundi, R.H., Isabirye M., et al. (2020)} . Rodent
species composition, relative abundance, and habitat association in the
Mabira Central Forest Reserve, Uganda,'' \emph{Journal of Vertebrate
Biology} , 69(2).

\textbf{R core Team (2013).} R: A language and environment for
statistical computing. R foundation for statistical computing, Viena,
Austria. URL http://www.R-project.org/.

\textbf{Tews, J., Brose, U., Grimm, V, et al.} \textbf{(2004)} . Animal
species diversity driven by habitat heterogeneity/diversity: the
importance of keystone structures. \emph{J.Biogeogr} (31): 79-92.

\textbf{Thorn, E., and Kerbis Peterhans. J. (2009)} . Small Mammals of
Uganda. \emph{Bonner zoologische.} monographienNr. \textbf{55:} 1-164
Editor: Karl-L. Schuchmann\emph{.}

\textbf{Thomas Puttker, Adriana A. Bueno, Camila dos Santos de Barros,
et al. (2013).} Habitat specialization interacts with habitat amount to
determine dispersal successof rodents in fragmented
landscapes.\emph{Journal of Mammalogy} , 94(3):714- 726. 2013.
http://dx.doi.org/10.1644/12-MAMM-A-119.1

\textbf{Thomas, M and Richard, S (1999).} Rainfall and rats:
Climatically-driven dynamics of a tropical rodent
population.\emph{Australian Journal of Ecology} (1999) 24, 80--89.

\textbf{Umetsu F, Naxara L, and Pardini, R (2006)} . Evaluating the
efficiency of pitfall traps for sampling small mammals in the
neotropics. J Mammal 87:757--765

\textbf{Waswa, S.B., Kityo, R., Kerbis J.P, et al. (2016).} Factors that
affect distribution of small mammal communities in Mabira Central Forest
Reserve (MCFR) and Kibale Forest National Park (KFNP). DOI:
10.13140/RG.2.2.14915.14885.

\textbf{Ward-Fear, G., Brown, G.P., Pearson, D et al.
(2021)\emph{.}}Untangling the influence of biotic and abiotic factors on
habitat selection by a tropical rodent. \emph{Sci Rep} \textbf{11} ,
12895 (2021).

\textbf{7.0 Figures and Tables}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1:} Map of MCFR zoomed out from the map of Uganda to
illustrate the survey area and the stratified sample locations in detail\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2:} Rarefaction curves comparing sample size and species
accumulation for the different survey areas in Mabira Central Forest
Reserve\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Figure 3:} Community structure of rodents and shrews in MCFR
along a degradation gradient\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Figure 4:} Temporal fluctuations in abundance of four most
common rodent species in MCFR, (a) in forested habitats (b) in adjacent
habitats such as fallows and plantations\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Figure 5:} Relationship between Species abundance and mean
monthly rainfall along a degradation gradient in Mabira Central Forest
reserve\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\textbf{Figure 6:} Relationship between mean monthly species abundance
for the most abundant species and mean monthly rainfall in Mabira
Central Forest reserve

\textbf{Table 1:} Rodent and shrew species composition and number of
captured specimens along a degradation gradient in Mabira Central Forest
Reserve\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{Species name} & \textbf{Adjacent habitat} & \textbf{Degraded
Forest Edge} & \textbf{Primary forest interior}\tabularnewline
\midrule
\endhead
\emph{Aethomys hindei} (Thomas, 1902) & 36 & - & -\tabularnewline
\emph{Arvicanthis niloticus} (clade C2 Bryja \emph{et al.} 2019) & 12 &
- & -\tabularnewline
\emph{Cricetomys ansorgei} (Thomas, 1904) & - & 1 & 9\tabularnewline
\emph{Deomys ferrugineus}(Thomas, 1888) & - & - & 4\tabularnewline
\emph{Gerbilliscus giffardi} (Aghova \emph{et al.} 2017) & 24 & 1 &
-\tabularnewline
\emph{Grammomys kuru} (Thomas Wroughton, 1907) & - & 1 &
-\tabularnewline
\emph{Hybomys lunaris} (Pradhan \emph{et al.} 2022) & - & 3 &
4\tabularnewline
\emph{Hylomyscus stella} (Nicolas \emph{et al.} 2021) & 11 & 116 &
192\tabularnewline
\emph{Lemniscomys striatus} (clade E H\selectlanguage{ngerman}ánová \emph{et al.} 2021) & 139 &
17 & -\tabularnewline
\emph{Lophuromys stanleyi} (Onditi \emph{et al.} 2021) & 104 & 30 &
7\tabularnewline
\emph{Lophuromys ansorgei} (de Winton, 18964) & 53 & 2 &
3\tabularnewline
\emph{Malacomys longipes} (Bohoussou \emph{et al.} 2015) & - & - &
1\tabularnewline
\emph{Mastomys erythroleucus} (clade C H\selectlanguage{ngerman}ánová \emph{et al.} 2021) & 62 &
1 & 1\tabularnewline
\emph{Mus minutoides} (Smith, 1834)\textsuperscript{1} & 35 & 3 &
1\tabularnewline
\emph{Mus bufo} (Thomas 1906) & 11 & 1 & 1\tabularnewline
\emph{Oenomys hypoxanthus} (Pucheran, 1855) & 1 & - & -\tabularnewline
\emph{Praomys jacksoni} (clade Ib Mizerovsk\selectlanguage{ngerman}á \emph{et al. 2}019) & 17 &
118 & 185\tabularnewline
\emph{Praomys missonnei} (clade IV Nicolas \emph{et al.} 2011) & - & 14
& 15\tabularnewline
\emph{Rattus rattus} (Linnaeus, 1758) & 88 & 3 & -\tabularnewline
\emph{Crocidura luna} (Dollman, 1910) & 12 & 1 & 1\tabularnewline
\emph{Crocidura turba} (Nicolas \emph{et al.} 2019) & 22 & 4 &
-\tabularnewline
\emph{Crocidura olivieri} (clade IV-A Jacquet \emph{et al.} 2015) & 20 &
4 & 4\tabularnewline
\emph{Crocidura} cf \emph{macmillani} (Dollman 1915)\textsuperscript{2}
& 6 & - & -\tabularnewline
\emph{Scutisorex congicus} (Thomas 1915)\textsuperscript{3} & 1 & 1 &
8\tabularnewline
\textbf{Total number of mammals from each site} & 654 & 321 &
437\tabularnewline
\textbf{Trap success (\%)} & 10.7 & 7 & 5\tabularnewline
\textbf{Number of species} & 19 & 19 & 16\tabularnewline
\textbf{Species diversity (H')} & 2.4 & 1.7 & 1.3\tabularnewline
\bottomrule
\end{longtable}

\textsuperscript{1}As in Bryja et al. 2014 this species may as well
represent \emph{M. cf. gratus} , which was confirmed in both Minziro and
Kakamega forests (Bryja et al. unpublished data), the two species are
morphologically similar with only genetic data the able to tell them
apart.

\textsuperscript{2} \emph{C. macmillani} is now considered an endemic
species in southern Ethiopia, but Malahat and Bryja et al. (unpublished
data) have genomic data showing that genetically very similar taxon
occurs also in Uganda.

\textsuperscript{3} In the field identified as \emph{Scutisorex
somereni,} but genomic data revealed it's very similar to \emph{S.
congicus} from Semliki (FMNH data).

\selectlanguage{english}
\FloatBarrier
\end{document}

