Introduction
ROE DEER Jaecol 1996
Variation in home range size has long been a subject of ecological interest. Interspecific
variation in home range size has been related to body-size-dependent metabolic requirements
(McNab 1963), declining rates of utilisable energy in the environments with increaing body
weight (Harestad & Bunnell 1979), species overlap (Damuth 1981), biological time
(Lindstedt, Miller & Buskirk 1986) and rate of home range use (Swihart, Slade & Bergstrom
1988)
Intraspecific variation in home range size is less well understood.
Variation in home range size H can be caused by both individual variation in metabolic
requirements R(due to e;g;body weight, difference in new borns) or by spatial variation in
productivity of the environment P (Harestad & Bunnell 1979, authors of roe deer 1996).
Thus, minimum home range size is a functionof habitat productivity and resource distribution
as well as individual energy requirements (H and B 79), so homerange size is one indicator of
habitat quality (roe deer authors).
Buzzard dispersal
(smaller ranges indicate thet the habitat was better and/or that the individuals were of high
quality)
Range characteristics can indicate the quality of an animal. Previus studies have found that
range size declines with increased food availability in mammals (e.g. Boutin 1985, Kenward
19!5, Wauters and Dondt 1992, Tew 1992, Wiegand 1995, Lucherini and Lovari 1996, Tufto
et al 1996, Corp et al 1997, Hubbs and Boostra 1998) and birds (Kenward 1982, Newton
1986, Johns(one 1992, Babcock 1995, Zabel et al 1995, Marzluff et al. 1997). Moreover,
range size is inversely related to survival, weight and breeding success in squirrels (Kenward
1985, Wauters and Dhondt 1992); This adds credence to the assumption that better
individuals exploit denser or richer food sources and consequently should have smaller home
ranges.
Schoener/anolis lizards (also see here in relationship between pop density and home range
size)
Home range size may be adjusted i relation to number of mates or intruder pressure (pop
density – Schoener 1982)
In certain territorial birds and lizards , population density and home range size are inversely
correlated, and the latter seems affected by food supply (e.g, Krebs 1971, Simon 1975)
We analyze within site variation to test for three hypothetical benefits of a larger home range
1 faster growth (possibly related to more food resources), 2 greater survival (possibly related
to more hiding places or more food) and for males, more females within the range
(presumably indicating 3 higher reproductive success)
Second paper intro
C;FERN Bird study 43 Woodpeckers (for your conservation paper)
For many tropical forest turdus species, their distribution depends on the size and quality of
forests (Birds of africa, etc). The Taita Thrush, one of the most endangered bird species in the
world (Collar ), need sizeable and less altered mist forests of Taita Hills, where its endemic (
). These fragmented chain of forests are under increasing threat
The secretive character of the Taita Thrush, together with its specialized use of habitat, result
in low densities over its range and great sensitivity to environmental changes.
The future conservation of the TT must be closely and strctly related/tied to future forestry
policy and the size and quqlity of Thills..Cosequently, a close study of the biology of these
species with special attention to factors influencing their distribution and density is urgently
required.
(here your paper can use mist netting data to calculate densities and validate distribution only
in the three fragments, also paper can discuss the general ecology) Once this is done (ie find
out the results that the thrush is only found in ‘frags and that densities are low in small and
distirbed frags, then i can go ahead now and look at the mechanisms that result in low
densites and absence in some fragments (mechanims by addressing territoriality and relattion
to habitat structure) then after this two papers, go ahead and look at the habitat use as
prerequisite to reccomending stuctures in forest to be preserved e;g; undergrowth etc.
Study Area
Study species
This study was carried out in the tropical montane cloud forests of Taita Hills, south east
kenya.
The study areas are situated in
The Ngangao study area comprises 92 ha
LL 99 Royal soc
The Taita Hills (03 20’S, 38 15’E and maximum altitude 2209m) lie in south-eastern
Kenya, 150 km inland from the Indian Ocean and are isolated from other highland blocks by
dry plains at 700 m altitude. At present, less than 400 ha of indigenous cloud forest is retained
in the three larger fragments (Chawia (CH,50ha), Ngangao (NG, 92ha° and Mbololo
(MB,220ha)) and nine tiny remnants (2-4 and one of 12 ha) (Brooks et al; 1998; Lens et al
1999). The mutual distances between the three main fragments are NG-MB 11.3km, CH-MB
19.4 km and CH-NG 10.9 km. The forests are included in an endemic bird area with the
Eastern Arc Mountains of Tanzania (Stattersfield et al 1998), although they are
biogeographically rather distinct from these (Brooks et al 1999). Indigenous forest loss since
th early 1960s has been very substantial and is estimated at 85% for CH, 50%for NG, <50%
for MB and 95-99% for some of the smallest remnants (Beentje 1987). The three forest
fragments differ considerabley in quality (Wilder et al 1999). The least disturbed fragment
(Mbololo, 200 ha) has more biomass, higher eqitability, greater canopy cover, more open
shrub layer, higher leaf litter cover and less herbaceous cover than the intermediate (Ngangao,
92 ha) and most disturbed ones (Chawia, 50 ha).
Methods
Vegetation data:
Vegetation data were recorded in 10-m radius circular plots, based on a 25-m grid of the 9-ha
plot. Within each 10-m circular sampling plot, counts were made of the number of small and
large trees….. Estimates were made of the percentage cover area covered by litter, herbs, bare
ground….. and the presence of paths and ….. the average gradient / slope recorded.
Each measure was then averaged over 10-m circular plots and linked to a Geographical
Information System (GIS)
Finally, for each territory, vegetation variables were estimated by over-laying territorial
boundaries
Auk/tanagers
Vegetation measurements produced sets of 20 variables. Because many of the variables were
highly correlated with one another, we used principal component analysis (PCA) to simplify
the structure of the data sets by reducing them to a smaller set of uncorrelated variables that
accounted from a large part of the variation in the original data set. PCA was performed on
correlation matrices, and resulting factors (axes) with eigenvalues >1 were used in analysis of
habitat charcteristics and hR variables. The extent to which the original variables were
correlated with the components (factors loadings)) was used to interpret each axis.
The 20 habitat variables considered were subjected to a principal components analysis (PCA)
by means of STATS programme (stats,Inc). The PCA was performed with varimax rotation
and we selected sufficient number of axes to account for two-thirds of the total variance
accumulated. Subsequently, the 7 forest plots were plotted onto the plane taken from the first
and second axes with the 20 variable eigenvalues represented as vectors.
In the PCA performed on the 7 forest plots in rtelation to the 20 habitat variables, 67.7 % of
the tootal variance was accounted for by the first two axis (Table ). The first principla
See LL royal Veg anal.
Measuring smaller quadrats
We chose four points in a stratefied random manner (one on each direction – north west,
north-east, south-west and south east) at which to establish four 1 X 1-m quadrats. In these
quadrats we estimated the percentage cover of leaf litter, herbaceous growth and also
measured litter depth. We then averaged the four scores to obtain a single value for the
samlping point
Trapping and handling
From September
were carried out
until
and
from
until one week trapping sessions
From 1997 to 1999, 40 thrush were fitted with radio transmitters (Biotrack,Wareham, Dorset,
UK) (were equiped with an 80-g transmitter fitted to an elastic harness
Each transmitter operated at a unique frequency within 173Mhz band.
All birds were adults
The birds were banded with numbered aluminium bands and unique three color combination
of plastic bands.
The transmitters did not appear to affect the flight or behaviour patterns of the birds. Indeed
95 % of the birds were recaptured at least once, a week or more later.
At capture a thrush was weighed and its body condition measurements were taken.
Information about age and reproductive status was recorded.
Where possible, sex was determined by wing-chord length (males mm; females mm;
from Luc et al 199 ).
Radio-tracking
Of each radio-tagged thrush, two poin-fixes were taken per day, with a minimum time interval
of 2h between fixes. Between 30 and 40 fixes were (mean ) taken for each individual. This
number/range is chosen because a plot of home range size against the number of fixes reach
an asymptomic value at about 30 fixes. Only when these minima were equalled or exceeded
was a bird included in the analysis. The location of a thrush was recorded using west – east
and north – south coordinates with an accuracy of 5 m. All tracking was done betwen 0600
am and 0600 pm.
To represent all times of the day, tracking was split into several periods
Birds are known to have vary their general activity with period of the day.
Over the course of a day, the activities of birds usually varies. Consequently, the day was
divided into three periods of equal number of hours: morning , afternoon, evening.
Estimation of Population Density
The population density was estimated using capture-recapture techniques
As birds were caught by use of mist-nets, which are unbiased ( ), the assumption of equal
probability of recapturing marked and capturing unmarked birds should be. Also, because
only the relative population density is of interest in this study, some bias in the estimates due
to violation of this assumption can be tolerated. (find other assumptions).
The estimated population sizes were
Estimation of Invertebrates abundance
We chose four points in a stratefied random manner (one on each direction – north west,
north-east, south-west and south east) at which to establish four 1ft X Ift plots. In these
quadrats we removed leaf litter (simulating the thrushes) by placing it on the side, till we
reached bare ground. We counted all invertebrates larger than 3 cm in size encountered during
litter removal and those that were on or even slightly below the ground. We then averaged the
scores to obtain a single value for each variable for the sampling point. .
Analyses
Stats
Most of the following analyses employed multiple regression in the form of generalized
lineaer models. (assumptions made)
Multiple regression was used to investigate which variables influenced home range size. The
stepwise method of adding and removing variables until a model is reached where no more
variables are eligible for entry or removal was used (Norusis 1993 in JAEcol 96 , 715 )
Because many of the explanatory variables used in the analyses were co-linear, simple stepwise models have been avoided. Rather, the regression models are presented as stages in the
step-wise procedure, ith all explanatory variables at each stage added independently (not
cumulatively). Interpretation of the models and the inclusion of significant variables at a
second or third stage depended on the aims ot the relevant analyses and the biological
implications of the findings.
The Wald test was used to test main effects and interactions of habitat and sesaon on range
size
Home range
All data on home range size were calculated using the RANGES V program (Kenward 199 ).
For each thrush, a utilization distribution was calculated that allowed us to determine
wheather it had a mono- or multinuclear range (Kenward & Hodder 1995). Since they had
multinuclear ranges, multinuclear clustering (Kenward 1990?) was used to calculate home
range size.
Multinuclear Probability Polygon method (Kenward 90) uses a joining rule that initiates
clusters at three location points.
Results
PCA analysis
In the PCA performed on the 7 forest plots in relation to the 20 habitat variables, 66 % of the
total variance was accounted for by the first two principal axes (Table 1). The first principal
component accounted for 34 % of the variance and represents canopy height and cover (
Table ). This first axis describes the plots in relation to their (see Bird study 43, 305 , also has
pcs graphed against forest plots)
Home range size variation
The partial regression coefficient between home range size and food supply was significantly
negative, indicating that roe deer increase their home ranges in response to decreasing food
supply (Table- showing the partial correlations Jaecol 96 715 see reporting style here. Its like
report and interpret)
Discussion
Pop density
Were individuals to occupy completely contiguous, exclusive areas, and exact relation would
exist between home-range area and population density; H=aD-1 (Damuth 1981; Schoener 1
Schoener 1982)
H= Home range area, D=density a= proprtionality constant to make the units commensurate
(density is numbers per square metre and homerange is sq; meter, thus the constant a is 1.)
N;B a perfect relationship in pop density and Homerange size is an indirect indicator of the
degree of territoriality.
How about in overlapping home ranges?
If no relatinship between HR size and density is found, then that implies that home range size
must increase with increasing population density. Interestingly, and in contrast with the often
held idea that homerange (and territory) size decreases with increasing population density,
Tufto et al 1996, found that there was a strong tendency for home ranges size to increase with
increasing population density.
Tufto also found out that in habitats with sparser cover, home ranges were larger.
Points for discussion
Thrushes adjust the sizes of their home range in response to decreasing food supply,
suggesting that metabolic requirements do strongly influence home range size (point out if
any precautions should be held on the behaviour of the species or the statistics used when
interpreting this)
Home range size also appear to be influenced by PC1 (cover etc), supporting the hypothesis
that cover is important in reducing adult mortality.
Effects of PC 1 (carries Shrub area)
From Roe deer pg 715
Traditionaly, in foraging-predation trade-off models (Krebs & Kacelinck 1991), availability
of cover is important in that it reduces the risk of predation and thereby increases the survival.
Thus a high quality home range is expected to reduce the risk of predation and hence increase
survival and fitness. Cover is hence an important component of an individuals range, and one
would predict a positive relationship between the size of a range and visibility (as measured in
the form of cover).
Habitat heterogeneity is believed to be important for several reasons. If less of two resources
is required when taken together than when included separately (e.g; food and cover, or
different nutrients), then these resources are said to be complimentary (Tilman 1982). As an
effect of this we would expect a decrease in home range size if different resources are
available inside a home range.