Julie Adamo
INLS 720/Metadata
Final Project
December 2009
Report on the SNIP-IT Experiment
Article #1:
Cooley, H. S., Wielgus, R. B., Koehler, G. M., & Robinson, H. S. (2009). Does hunting regulate cougar populations? A test of the compensatory
mortality hypothesis. Ecology, 90(10), 2913-2921.
Author keywords: carnivore; compensatory mortality hypothesis; cougar; density; emigration; hunting; immigration; mortality; population
growth; Puma concolor; source–sink; survival.
Biosis concept codes: 00512, General biology - Conservation and resource management; 07502, Ecology: environmental biology - General and
methods; 07508, Ecology: environmental biology - Animal; 07518, Ecology: environmental biology - Wildlife management: terrestrial; 62800,
Animal distribution
Biosis taxonomic data: Carnivora, Mammalia, Vertebrata, Chordata, Animalia, Animals, Carnivores, Chordates, Mammals, Nonhuman
Vertebrates, Nonhuman Mammals, Vertebrates Felidae [85770] Puma concolor, cougar, mature, immature, female, male
Biosis geographic data: Washington; USA; North America; Nearctic region
Biosis miscellaneous descriptors: population density, population growth, species survival, population survival, density-dependent response,
species reproduction, hunting effect, compensatory mortality hypothesis
Brief description of data object 1: This chart describes the causes of death of cougars who were radio-collared for the study. Results are broken
down by sex and age.
Brief description of data object 2: This chart shows survival rates for cougars and the number of days they were collared for. Results are broken
down by sex and age
SNIP-IT structure: Captions and footers are included in their entirety. Paragraph selections begin with the sentence that includes mention of the
figure and the two sentences following.
Threshold: .3
SNIP-IT
Divergences
Comments
CAPTION, DATA OBJECT 1: Sources of
mortality of radio-collared cougars in
northeast (HH, heavily hunted) and
central (LH, lightly hunted)
Washington State, 2002–2007.
sources 0.17279659654867222
central 0.14745502729191193
heavily 0.14745502729191193
northeast 0.14745502729191193
state 0.14745502729191193
washington 0.14745502729191193
mortality 0.12947489776367563
cougars 0.051177212232715125
lh 0.03547006046515849
These results mirror many of both the Biosis
and author supplied terms, but the most
relevant terms have the lowest divergences.
However, “heavily hunted” and “lightly
hunted” are elements of this dataset that are
not included in any of the indexing and are
aspects of the data that could be very
interesting/useful to other researchers.
FOOTER, DATA OBJECT 1: Note:
Sample sizes (n ¼ total number of
animals at risk), mortality rates
(mean 6 SD), and number of
mortalities (in parentheses) are
shown.
PARAGRAPH 1, DATA OBJECT 1: We
observed 26 unmarked kittens (six
number 0.34559319309734443
note 0.2161182953336688
risk 0.2161182953336688
sizes 0.2161182953336688
animals 0.17279659654867222
parentheses 0.17279659654867222
sample 0.17279659654867222
total 0.17279659654867222
mortalities 0.14745502729191193
rates 0.14745502729191193
mortality 0.12947489776367563
sd 0.12947489776367563
mean 0.03904246133015528
males 0.062299706978479495
causes 0.0506454009759239
Note also that hyphenated words were not
included in the divergences.
The important terms here, animals and
mortality, are represented in the Biosis terms.
However, the “number at risk” element is not
represented. I’m not sure how useful this
element would be, however.
This SNIP-IT describes some of the causes of
death that are represented in data object 1,
females, two males, nine of unknown
sex in HH; three females, four males,
two of unknown sex in LH) traveling
with collared females. Fifty-three (35
in HH, 18 in LH) radio-collared
cougars died during the study (Table
1). Hunters killed 26 cougars, 22 died
from natural causes, three died in
vehicle collisions, and two were killed
from depredation hunts. Eight
juveniles (two in HH, six in LH)
emigrated and were censored at the
last known date of their location.
collisions 0.0506454009759239
date 0.0506454009759239
depredation 0.0506454009759239
hunters 0.0506454009759239
hunts 0.0506454009759239
juveniles 0.0506454009759239
last 0.0506454009759239
location 0.0506454009759239
vehicle 0.0506454009759239
lh 0.03756857723236393
females 0.03728750847200635
natural 0.035897588623584636
sex 0.03280408227380097
but not explicitly mentioned in the caption.
The causes of death are not represented in
any of the indexing, and are useful data
sources.
CAPTION, DATA OBJECT 2: Radio-days
and survival rates (mean 6 SD) by sex
and age class for radio-collared
cougars in northeast (HH, heavily
hunted) and central (LH, lightly
hunted) Washington State, 2002–
2007.
central 0.08679891056440098
class 0.08679891056440098
heavily 0.08679891056440098
northeast 0.08679891056440098
rates 0.08679891056440098
state 0.08679891056440098
washington 0.08679891056440098
sd 0.07429099437084528
survival 0.049959873156261686
sex 0.03445226689805594
The “survival” subject and Washington
location are well-represented in the indexing.
FOOTER, DATA OBJECT 2: Sample size
n is the number of mortalities, with
the total number of monitored
animals in parentheses.
number 0.7422465977071815
size 0.4481396522491403
animals 0.37112329885359074
parentheses 0.37112329885359074
sample 0.37112329885359074
total 0.37112329885359074
mortalities 0.3260716201749059
survival 0.1601934141873012
adult 0.05786594037626732
Same as caption above.
PARAGRAPH 1, DATA OBJECT 2: Six of
the ‘‘natural’’ kitten mortalities in HH
The divergence results here reflect the
importance of the difference of male/female
(three females, two males, one
unknown sex) were presumed to
have been killed by male cougars, as
confirmed by canine tooth punctures
in the skull and close proximity of a
collared male at estimated time of
death. Average annual survival rates,
including all sources of mortality, for
all radio-collared cougars in HH were
0.56 6 0.05 (mean 6 SD) and 0.71 6
0.06 in LH, but survival varied with
age and sex classes (Table 2). Overall
survival and survival of adults was
higher in LH than in HH (overall: Z ¼
1.98, P ¼ 0.02; adults: Z ¼ 1.75, P ¼
0.04). Survival of adult females and
survival of kittens was also higher in
LH (adult females: Z¼1.88, P¼0.03;
kittens: Z ¼ 1.49, P ¼ 0.07).
adults 0.05786594037626732
overall 0.05786594037626732
kittens 0.04611332854704516
male 0.04611332854704516
females 0.03903315888317881
survival, which is also represented in the Biosis
indexing through a combination of taxonomic
and concept data.
Article #2:
Stamps, J. A., Krishnan, V., & Willits, N. H. (2009). How different types of natal experience affect habitat preference. American Naturalist,
174(5), 623-630.
Author keywords: NHPI, habitat preference, learning, Drosophila, genotype, natal disperser
Biosis concept codes: 07502, Ecology: environmental biology - General and methods; 07506, Ecology: environmental biology - Plant; 07508,
Ecology: environmental biology - Animal; 64076, Invertebrata: comparative, experimental morphology, physiology and pathology - Insecta:
physiology
Biosis taxonomic data: Insecta, Arthropoda, Invertebrata, Animalia; Animals, Arthropods, Insects, Invertebrates; Diptera [75314]; Drosophila
melanogaster; Monocotyledones, Angiospermae, Spermatophyta, Plantae; Angiosperms, Monocots, Plants, Spermatophytes, Vascular Plants;
Musaceae [25365]; banana
Biosis methods and equipment data: Bayesian model; mathematical and computer techniques
Biosis miscellaneous descriptors: genotype, habitat preference, pest management, metapopulation dynamics, conservation biology, sympatric
speciation, natural habitat, captive environment, natal habitat preference induction
Brief description of data object 1: A graph showing how quality of experience (positive/negative) in a natal habitat influences the attractiveness
of similar characteristics in other environments
SNIP-IT structure: The structure for this sample contains three sentences: the one prior to mention of the figure, the one including mention of
the figure, and the one following.
Threshold: .3
SNIP-IT
Divergences
Comments
CAPTION, DATA OBJECT 1: How experience in the natal
habitat and survival to the age/stage of dispersal affect
the relative attractiveness of cues from the natal
habitat w. Log V indicates the association between
natal experience E and environmental state: values
above 0.0 indicate that experience E is “good” (more
likely to occur under a favorable state), while values
below 0.0 indicate that E was “bad” (more likely to
occur under an unfavorable state). The variable Q
indicates the extent to which survival to the age/ stage
of dispersal, S1, is more likely to occur under a
favorable environmental state. Values of w 1 1.0
indicate that cues from habitat X are more attractive to
individuals raised in habitat X than to naive individuals;
values of w ! 1.0 indicate the reverse.
values 0.17510352628857598
state 0.1590498706516039
age 0.10377036746861457
stage 0.10377036746861457
habitat 0.08430513166145723
favorable 0.08333734251797494
cues 0.07604448024621675
individuals 0.07604448024621675
dispersal 0.06987845305312643
survival 0.06453719734814552
association 0.05999448589647058
extent 0.05999448589647058
log 0.05999448589647058
reverse 0.05999448589647058
s1 0.05999448589647058
unfavorable 0.05999448589647058
The divergence results here picked up a few
important concepts such as “habitat” and
“survival.” But one important aspect of this data
set is the stage at dispersal, and this subject is
not reflected in the Biosis indexing, but is
reflected somewhat in the divergences.
variable 0.05999448589647058
environmental 0.05982587592189017
attractive 0.046131542285271665
how 0.046131542285271665
experience 0.041828352109768964
affect 0.038022240123108376
natal 0.032579311320133475
relative 0.03226859867407276
PARAGRAPH 1, DATA OBJECT 1: Values of w above 1.0
indicate that dispersers born and raised in habitat X find
new patches of habitat X to be more attractive than is
the case for naive dispersers, while values of w below
1.0 indicate the reverse. Equation (3) can be expanded
to separate the effects of S and E on w (see app. A in
the online edition of the American Naturalist; fig. 1).
We can specify the effects of S on w by Q, where Q p P
/P .
PARAGRAPH 2, DATA OBJECT 1: As expected, stronger
positive associations between survival and the
favorable environmental state (indicated here by Q)
increase the relative attractiveness of cues from habitat
X, as do stronger positive associations between natal
experience and the favorable environmental state
(indicated here by positive values of logV). However,
contrary to previous suggestions (e.g., Stamps and
Davis 2006; Stamps and Swaisgood 2007), the effects of
good and bad experiences on relative attractiveness are
asymmetrical, in the sense that the positive effects of
good experience on cue attractiveness are stronger
dispersers 0.13622976221654645
values 0.08263891886688257
app 0.07800427398896016
born 0.07800427398896016
case 0.07800427398896016
patches 0.07800427398896016
effects 0.06470112471442806
american 0.06109824519481516
attractive 0.06109824519481516
edition 0.06109824519481516
naturalist 0.06109824519481516
online 0.06109824519481516
new 0.03430282351998321
positive 0.14671244429898989
attractiveness 0.10882895657584517
associations 0.08602700677787509
sense 0.08602700677787509
stamps 0.08602700677787509
relative 0.0643661573853768
effects 0.06030596006712073
cue 0.05739292140680774
favorable 0.05739292140680774
bad 0.056832148872415014
dispersal 0.046878164012394835
contrary 0.04301350338893754
This SNIP-IT is referring mostly to the equations
they used in the study. Biosis has included
indexing describing the methods used in this
study, specifically the Bayesian model. The
authors do not include information about this in
their keywords. The divergences for this SNIP-IT
are not very useful.
This SNIP-IT does not offer much new content in
terms of subject matter, everything here is
represented in previous SNIP-ITs.
than the negative effects of bad experience on cue
attractiveness (fig. 1). Upon further reflection, this
result makes intuitive sense, since even individuals who
had bad experiences before dispersal must have also
survived to the age/stage of dispersal.
PARAGRAPH 3, DATA OBJECT 1: Since we have assumed
that survival is typically more likely to occur if the
environmental state is favorable (Q = 1.0), negative
effects of natal experience on cue attractiveness are
likely to be counteracted by the positive effects of
survival on cue attractiveness. In contrast, the positive
effects of good natal experiences and survival on cue
attractiveness complement one another and in
combination can lead to sizeable increases in the
relative attractiveness of cues from the natal habitat
(fig. 1). By extension, these results imply that
asymmetrical effects of good versus bad natal
experiences on habitat preference will be strongest for
species in which offspring survival is strongly affected
by environmental state (i.e., large
values of Q) and in which environmental state has a
strong influence on habitat quality (i.e., XFJ k XFK).
davis 0.04301350338893754
further 0.04301350338893754
intuitive 0.04301350338893754
logv 0.04301350338893754
previous 0.04301350338893754
reflection 0.04301350338893754
result 0.04301350338893754
suggestions 0.04301350338893754
swaisgood 0.04301350338893754
experiences 0.0427053079928785
environmental 0.03902458812861651
state 0.03275362889542429
negative 0.0321830786926884
survival 0.13493327320300888
attractiveness 0.11438787119536148
cue 0.11002196571486737
effects 0.1036101883138669
environmental 0.08158067547766806
state 0.07187080311659622
positive 0.05438711698511204
experiences 0.04510705013182879
combination 0.04491311153559005
complement 0.04491311153559005
increases 0.04491311153559005
natal 0.03971349773142323
contrast 0.03373331830075222
extension 0.03373331830075222
influence 0.03373331830075222
large 0.03373331830075222
negative 0.03373331830075222
quality 0.03373331830075222
xfj 0.03373331830075222
xfk 0.03373331830075222
This SNIP-IT brings in the element of difference
between species, though specific species are not
mentioned in this clip. Taxonomic data is
reflected in the Biosis indexing. The term
“species” does not appear in the divergence
results.
The most important concept here, “habitat
preference”, is reflected in the biosis indexing.
PARAGRAPH 4, DATA OBJECT 1: By extension, these
results imply that asymmetrical effects of good versus
bad natal experiences on habitat preference will be
strongest for species in which offspring survival is
strongly affected by environmental state (i.e., large
values of Q) and in which environmental state has a
strong influence on habitat quality (i.e., XFJ k XFK). In
such species, even very bad experiences in the natal
habitat are unlikely to reduce the attractiveness of
habitat-specific cues much below their attractiveness to
naive individuals (cf. the results for Q p 6.0 in fig. 1).
Possible examples include insects in which natal
dispersers seek new habitats in which to lay their eggs
and that lack parental care.
results 0.06910577886945633
species 0.061789596859154375
habitat 0.05606316636216721
experiences 0.04637964180191714
care 0.04591595796849776
cf 0.04591595796849776
eggs 0.04591595796849776
examples 0.04591595796849776
insects 0.04591595796849776
parental 0.04591595796849776
possible 0.04591595796849776
environmental 0.042517902927937355
attractiveness 0.03593853586360452
state 0.03593853586360452
extension 0.034552889434728166
influence 0.034552889434728166
large 0.034552889434728166
quality 0.034552889434728166
xfj 0.034552889434728166
xfk 0.034552889434728166
This SNIP-IT is very similar to the previous one,
and elaborates on differences between species.
This one does mention certain types of insects
specifically. The Biosis taxonomic data, and to
some extent the author supplied keywords,
reflect this concept.