Tailed Frog Tadpole
Population Estimation Methods,
Wildlife Habitat Area Monitoring
Pilot Project, 2005
Prepared by
Prepared for
Les W. Gyug, R.P.Bio.
Ecosystems Branch,
Okanagan Wildlife Consulting
B.C. Ministry of Environment,
3130 Ensign Way,
Victoria, B.C.
Westbank, B.C. V4T 1T9
(250) 769-5907
Les_Gyug@shaw.ca
November 21, 2005.
ABSTRACT
This was a pilot project to test the differences in precision and accuracy of different sample
segment lengths, different sampling intensities over different stream lengths using “rubble-rousing” instream population estimation methods for tailed frog tadpoles to help design methods for monitoring of
tailed frog Wildlife Habitat Areas (WHAs). The methods are presumed to be close to a complete census
of tadpoles in any sampled short segment (1-m to 5-m). From Sept. 19-Oct. 7, 2005, 8 stream reaches
from 100 to 300-m length were sampled in 7 WHAs that provided data on 1732 tadpoles observed.
Three stream reaches on 3 WHAs were not core reaches and only 1 tadpole was found on each of these
3 reaches. The study design compared the accuracy and precision of the following data sets:
1. 30-m of total sampling (30% intensity) on 100-m reaches (n=6 trials) using 30 1-m sample segments
covering the width of the stream, 10 3-m sample segments and 6 5-m segments randomly selected
independently but sampled concurrently,
2. 5-m segments sampled over 100-300 m (n=15 including multiple visits to reaches) marking the exact
m in which each tadpole was first observed to derive precision and accuracy of nested 1-m, 2-m, 3-m
4-m and 5-m segments for sampling over different lengths of stream reaches at different intensities,
and
3. multiple visits to 4 reaches (3 visits to 2 reaches, and 2 visits to 2 reaches) to estimate within-year
variability that would be due to the sample methods alone if the populations in the reaches were
closed and unchanging during the 3-week sampling period.
To monitor single reaches as representative of a WHA, at high tadpole population levels (>100
tadpoles per 100-m stream length) in relatively uniform stream reaches, monitoring a reach of 100-m at 30%
intensity usually produced acceptably low Standard Errors (SE) of 20-25% using sample segment length of 1m or 5-m. The SE of 3-m segments was 30% in our trials but it was not clear why this should have been
higher, and further trials may indicate 3-m segments can have SE as low as 1-m or 5-m segments on
average. At low population levels (<100 tadpoles per 100-m stream length) SE was much higher (50-80%),
and sample size needed to be increased to achieve an acceptable SE within 20% of the mean. Necessary
sample sizes to keep SE low in low population reaches would require sampling reaches >100 m no matter
what sample segment length was used.
5-m segments tended to be more efficient (more accurate, higher precision) at 15% intensities than
other segment lengths, but this advantage did not hold at 30% intensities. Sample segments of any length
may be used but 1-m segments tend to have upward bias at low intensities and in low densities, 3-m
segments did not perform well in precision in our trials, and 5-m segments performed poorly if there were
uninhabited sections of 10-15 m length within the monitored reach (which can be solved by choosing
uniform reaches to sample). Monitoring 200-300 m reaches by sampling 2 or 3 100-m reaches, which were
themselves subsampled, produced similar SE to the 1-m to 5-m segments on average, so that SE is not
assumed to be any function of sample segment length but is based on sampling effort/sample size in any
given site. Sample segment length for monitoring need not be set at one standard for the entire tailed frog
range since as long as population estimates are made reliably and accurately, only the final estimates, not
the within-reach variation, will be used for wide-area or for long-term comparisons. Short-term comparisons
within one WHA will require consistent sampling methodology within the sites being contrasted.
Extensive monitoring of WHA for tailed frog tadpoles is recommended at irregular intervals with
frequent (annual) sampling to establish baselines, sampling at relatively infrequent (e.g. 5-year) intervals
when impacts are not expected based on other indicators, and more frequent sampling when other
indicators show there is a higher probability of population changes. 50% total declines in tadpole
populations are proposed as one threshold to trigger more intensive monitoring based on being well
above natural within-year variation in most sites. Another separate threshold would be when entire
cohorts of tadpoles appear to be missing from, or have undergone precipitous declines in, a given
population.
TAILED FROG WHA METHODS 2005 DRAFT
2
OKANAGAN WILDLIFE CONSULTING
TABLE OF CONTENTS
INTRODUCTION .................................................................................................................. 5
Acknowledgements.................................................................................................. 6
STUDY AREA ........................................................................................................................ 6
STUDY DESIGN.................................................................................................................... 8
WHA Effectiveness Monitoring ................................................................................ 8
Study Design ............................................................................................................ 8
Field Methods ..........................................................................................................10
Study Design applied to the WHAs ........................................................................12
WHA and Reach Selection ...........................................................................12
Sample Site selection within Monitored Reaches ......................................12
Analyses...................................................................................................................14
RESULTS and ANALYSES....................................................................................................15
Comparison of Sampling Schemes with 30% Intensity .......................................16
Precision and Accuracy by Segment Length and Population Size ........................22
Contrast of Monitored Reach Length .....................................................................24
Do 100-m sub-reaches differ within longer reaches?................................24
Is anything gained by sampling reaches longer than 100 m?...................25
Sample one long reach, or multiple smaller reaches? ...............................26
Within-site Variation Within the Year ....................................................................27
Time-of-year Effect ......................................................................................27
Within-year Repeatability ...........................................................................29
Within-site Variation Between Years .....................................................................30
Tailed Frog Age Class Distribution .........................................................................32
Size Class Distribution of Tadpoles .............................................................32
Abundance of Adults ....................................................................................33
LONG-TERM MONITORING RECOMMENDATIONS ...........................................................35
Best Indicators Tailed Frog WHA Population Monitoring .....................................35
Power and Trend Analysis ......................................................................................36
Trend Analysis ..............................................................................................37
Sample-to-Sample Comparisons.................................................................40
Best Options for Tailed Frog Tadpole Monitoring..................................................41
Framing the Question ..................................................................................41
Recommendations .......................................................................................42
LITERATURE CITED ............................................................................................................44
TAILED FROG WHA METHODS 2005 DRAFT
3
OKANAGAN WILDLIFE CONSULTING
List of Figures
Figure 1. Coastal Tailed Frog Wildlife Habitat Areas (WHAs) in the Merritt TSA on the east slope of the
Cascade Ranges in southern British Columbia, 2005. ................................................................... 7
Figure 2. Accuracy (top graph, as absolute difference of sample estimate from best estimate as % of
best estimate), and precision (middle graph, Coefficient of Variation as %; bottom graph, Standard
Error as % of sample mean) estimated from 6 randomly selected trials of 100-m reaches dataset as
sampled using 1-m, 3-m and 5-m sample segments in 6 Coastal Tailed Frog WHAs on the east
slopes of the Cascade Ranges, B.C., Sept-Oct, 2005. ................................................................. 21
Figure 3. A)Coefficients of Variation (upper graph) and B)Accuracy and bias as percentage of final
estimate (lower graph) of tailed frog tadpole population estimates per 100-m stream length using
nested sample segment lengths from 1 to 5 m (n = 10 for each sample) for WHA stream reaches,
east slope Cascade Ranges, B.C., 2005. .................................................................................. 23
Figure 4. Between-year and mean within-year Coefficients of Variation (S.D./mean) for 10 tailed frog
populations in the Chilliwack River valley sampled by 10 5-m regularly-spaced segments within 100m reaches. Mean within-year data as summarized in Maxcy (2003) based on unpublished data
provided by John Richardson, and between year data from Richardson (2001). ............................ 31
Figure 5. Coastal Tailed Frog tadpole size class distribution for 7 WHAs on the east slope of the
Cascade Ranges, Sept. 19-Oct. 7, 2005..................................................................................... 34
List of Tables
Table 1. Wildlife Habitat Areas (WHA) sampled for Coastal Tailed Frogs in the Merritt Timber Supply
Area, east side of Cascade Range, British Columbia, 2005.......................................................... 17
Table 2 . Accuracy and bias of sample estimates compared to best available population estimates in 6
100-m reaches in Cascades Tailed Frog WHAs sampled at constant 30% intensity by 1-m, 3-m and
5-m sample segment lengths for tailed frog tadpoles, 2005. ......................................................... 18
Table 3. Precision of sample estimates estimated by Coefficients of Variation and Standard Errors in 6
100-m reaches in Cascades Tailed Frog WHAs sampled at constant 30% intensity by 1-m, 3-m and
5-m sample segment lengths for tailed frog tadpoles, 2005. ......................................................... 18
Table 4. Mean, minimum and maximum of Coefficients of Variation for estimated tailed frog tadpole
populations per 100-m stream length calculated based on 10 samples over 300-m stream lengths (5
to 15% sampling effort), east slope Cascade Ranges, B.C., 2005. ............................................... 22
Table 5. Tailed frog tadpole abundance compared among 100-m sub-reaches within longer reaches
using 5-m sample segments. ..................................................................................................... 24
Table 6. Precision (Coefficient of Variation and Standard Error as % of estimated mean) of tailed frog
tadpole abundance estimates within long (200 or 300-m) reaches using 5-m sample segments
compared to the use of 100-m sample sub-reaches each sampled with 5-m segments. ................. 28
Table 7. The number of samples (annual or less frequent) required before a 50% total tadpole population
change could be detected predicted by TRENDS regression power analysis as software. ............. 39
Table 8. The minimum detectable total percentage tadpole population reduction over an 11-year period
where α = β = 0.20 using different yearly sampling regimes as predicted by TRENDS regression
power analysis software. ........................................................................................................... 39
TAILED FROG WHA METHODS 2005 DRAFT
4
OKANAGAN WILDLIFE CONSULTING
INTRODUCTION
The Coastal Tailed Frog (Ascaphus truei) and the Rocky Mountain Tailed Frog (Ascaphus
montanus) are primitive stream-breeding amphibians limited to the wet mountain areas of western North
America. Within British Columbia the Coastal Tailed Frog is limited to the Coast and Cascade ranges, and
the Rocky Mountain Tailed Frog is limited to two drainages in the southern Rocky Mountains and
Columbia Mountains. Both species have been designated as Identified Wildlife under the Identified
Wildlife Management Strategy (IWMS) Forest and Range Practices Act (FRPA) of British Columbia
because of concerns for the effects of forestry practices on the habitat and populations of this species.
Under the IWMS, Wildlife Habitat Areas (WHA) may be set aside for either of these species in areas along
streams with no-timber-harvesting zones of 30-m on both sides of the streams, and an additional 20-m
zone of managed forest adjacent to the 30-m reserve zone.
Development of monitoring strategies to determine the effectiveness of creating WHAs for tailed
frogs has been underway since 2003. (The term tailed frogs will be used when referring to the two
species generically, with comments referable to one species or the other made specifically.) To date,
several drafts of the WHA effectiveness monitoring schemes have been developed but these have not
been finalized. Maxcy (2003) drafted a generic tailed frog WHA effectiveness monitoring scheme for both
species, and a Version 1 of a monitoring scheme more specific to the Rocky Mountain Tailed Frog was
drafted January 2005 (FREP 2005).
Maxcy (2003) recommended a pilot project be undertaken to test out the recommended
methods, in particular the species-specific monitoring methods for sampling tailed frog tadpoles.
Sampling directed at determining population size of adults is not possible with limited budgets and in
limited timeframes. Only one study has ever sampled populations of adults effectively (Daugherty and
Sheldon 1982) because repeated visits to a site and mark-recapture sampling are required since typically
only 3-15% of adults at a site will be observable on any given nighttime search. Up to this point in
British Columbia most tailed frog surveys had been wide-ranging reconnaissance-level surveys to
determine the extent of tailed frog distribution. These had most often been time-constrained searches
that give an indication of presence/absence and some measure of relative abundance but are not
correlated with actual densities derived from “rubble-rousing” searches (Quinn et al. 2004). Absolute
abundance surveys, or at least a relative abundance survey that is repeatable and reliable must be used
for making comparisons over time if we wish to judge the effectiveness of WHAs in maintaining tailed
frog populations. Area-constrained searches for tadpoles aimed at determining tadpole densities have
been used often in the past, particularly in the U.S. Pacific Northwest and in a number of research
projects at University of British Columbia, but it was not entirely clear exactly which sampling scheme
would be most efficient, i.e. have the highest precision, allow for repeatability, and be the most efficient
to accomplish. Typical present budgets and anticipated future budgets would probably allow for no more
than one day of sampling at any given WHA in any given year so that efficient but robust sampling
methods, with known, or at least predictable, reliability must be sought.
The size of samples to determine tadpole densities within a given stream reach have ranged from
as small as 0.1 m2 (Hawkins et al. 1988) to 10 linear stream meters (i.e. the entire width of the stream
for a length of 10 m, Bury and Corn 1991). In the national parks of the Pacific Northwest, samples for
tadpole density have been standardized at 1 linear stream m (e.g. Adams 2000). Maxcy (2003) used
TAILED FROG WHA METHODS 2005 DRAFT
5
OKANAGAN WILDLIFE CONSULTING
tadpole capture data sets from the Olympic Peninsula where 1-m linear stream samples were randomly
selected from 300-m reaches, and from the Chilliwack River drainage where 5-m samples were regularly
spaced over 100-m reaches to compare the variability and efficiency of the different sampling methods.
She was unable to recommend one sample length over the other based on the limited samples available
and the wide ranges of variation seen.
This purpose of this project was to compare the efficiency, variability, precision and accuracy of
different levels of in-stream sampling and of different sizes of in-stream samples for tailed frog tadpoles.
This was undertaken as a pilot project for Tailed Frog WHA effectiveness monitoring at the extensive
level, so that all samples were made within existing WHAs. The basic methods recommended by Maxcy
(2003) were adopted with additions or alterations made where it was thought to be appropriate, and
where possible, incorporating the Version 1 (FREP 2005) recommendations made for Rocky Mountain
Tailed Frog WHA effectiveness monitoring.
Acknowledgements
Funding for this project was provided by the B.C. Ministry of Environment, Ecosystems Branch,
Victoria, B.C. Irene Stewart and Kathy Paige, Ecosystems Branch, MOE, Victoria, and Wayne Erickson,
Forest Practices Branch, MOF, Victoria, initiated this contract. Kathy Paige served as contract monitor.
Bruce Ryder provided field assistance in collection of data.
STUDY AREA
The study area was near the eastern edge of the range of the Coastal Tailed Frog in the Merritt
Timber Supply Area (TSA) of the Cascades Forest District on the eastern slopes of the Cascade Mountains
(Figure 1). Fifteen Tailed Frog WHAs had been established along streams occupied by tailed frogs in this
area based on sampling from 2000-2002 (Gyug 2000, Gyug 2001, Gyug 2002). All WHAs are referred to
by their provincial designation number in the format X-YYY where X is the Ministry of Environment region
number and the YYY is a consecutive number assigned to a WHA (for any species) in the order it is
designated. Stream lengths within individual WHAs ranged from 800 to 4100 m. The longest protected
stream length within a WHA was 6300 m because the WHA contained a set of branched streams. Basin
areas drained by individual WHA streams ranged from 0.57 to 11.70 km 2. Stream orders of WHAs were
from 1st order to 4th order based on 1:20,000 TRIM mapping, which is a good approximation of actual
stream order based on conventional definitions, i.e., existence of stream channels. It should be noted
that TRIMI data was used for some streams, and TRIMII for others. TRIMII based on 1:20,000 aerial
photography mapped many more streams, and more accurately, than TRIMI based on 1:40,000 aerial
photography. In general, the TRIM mapping does not map the fine scale (<20 m) meanderings of these
streams. Additional information on each stream is in a data summary for the WHA effectiveness
evaluations that is separate from this report.
TAILED FROG WHA METHODS 2005 DRAFT
6
OKANAGAN WILDLIFE CONSULTING
U Lytton
%
Merritt
3-004
U
%
#
3-015
3-014
Aspen %
U
Grove
#
#
3-016
#
#
3-005
3-017
#
8-077
#
8-078 %
U
#
Tulameen
Princeton
8-011
8-082
8-081
Hope
U
%
U
%
#
8-080
#
#
#
8-012
#
#
#
8-079
8-013
Core Range Boundary
Tailed Frog WHAs
Highways
Parks
Merritt TSA
10
0
10 Kilometers
Figure 1. Coastal Tailed Frog Wildlife Habitat Areas (WHAs) in the Merritt TSA on the east slope of the
Cascade Ranges in southern British Columbia, 2005.
TAILED FROG WHA METHODS 2005 DRAFT
7
OKANAGAN WILDLIFE CONSULTING
STUDY DESIGN
WHA Effectiveness Monitoring
There are four hierarchical levels of effort for WHA effectiveness monitoring:
1. Routine (paper, GIS or office-based),
2. Extensive (field data collection and analyses covering many WHAs at a minimal level of
coverage),
3. Intensive (field data collection and analyses covering a smaller subset of WHAs at a more
intensive level usually triggered by a set of criteria or indicators that reach a certain threshold
during routine or extensive level monitoring), and
4. Applied research (very intensive studies with formal study designs that may or may not be
applicable directly to WHA effectiveness monitoring, and may, or may not, be triggered directly
by WHA effectiveness monitoring).
This pilot project was meant to test the methods applicable to the Extensive level of monitoring.
The results from this portion of this pilot project will only be applicable to tailed frog tadpole population
estimation per unit stream lengths or to density estimation per unit stream area if that is a variable of
interest. These methods will be applicable to any level of effort or monitoring whenever estimation of
in-stream tadpole population size is a requirement.
Study Design
This study was meant principally to address the following: Is there a most efficient (highest
power, most accurate, lowest effort) sampling scheme for long term monitoring of tailed frog tadpole
populations within a WHA that is repeatable and reliable?
Each single-stream WHA in the Cascades is between 800 m and 4100 m in length. WHAs that
contain multiple stream branches may be longer. It will not be possible within a one-day level of effort to
estimate tadpole density in an entire WHA. That would first require stratification of the entire WHA
stream by reach (areas of common gradient, confinement, and general stream morphology), and then a
separate density estimation for each reach. Within each reach, samples would have to be selected
randomly to estimate the population over the entire reach. The amount of sampling required to do this is
not within the range of extensive sampling which ideally should not involve more than one day of
sampling by a team of two or three poeple. However, using the results from this study, it might be
possible to estimate the levels of effort required to estimate density over longer reaches than considered
here.
The effort available for extensive level monitoring will usually be just one, and will necessarily
include some measurement of stream or biotic variables to measure structural and/or functional
indicators beyond species-specific measurements on tailed frogs. Therefore the most efficient method
possible using less than one entire field day would be preferred. Power analysis for long-term monitoring
programs can only be applied if we can reliably estimate several factors including (among others) the
TAILED FROG WHA METHODS 2005 DRAFT
8
OKANAGAN WILDLIFE CONSULTING
coefficients of variation and how they may vary with population size. Given the lowest achievable
coefficient of variation, power will then depend on the size or rate of population decline we would like to
detect, acceptable levels of significance, the number of years over which we would like to detect any
decline, and the long-term sampling intensity (i.e., the numbers of years between return sampling).
None of these final 4 variables are fixed, and they need to be estimated (preferably based on biologically
significant trends or data) to develop an efficient long-term monitoring program.
Before extensive monitoring begins, an initial stage of stratification of streams within a WHA
should be done by tailed frog reach according to the classification developed by Dupuis and Friele (2002).
This will consist of frontier reaches that are headwater reaches that are often small (<1.5 m bankful
width), steep, ephemeral, and usually do not contain tailed frog tadpoles, but may be very important for
adults; core reaches (which may be synonymous with natal reaches) where reproduction occurs and
tailed frog tadpole density is highest; and transient reaches that are low-gradient fish-bearing streams
where tadpoles may occur but usually only because they have migrated or been washed downstream
from core reaches. This stratification may have already been done for some WHAs and may change the
goals and objectives for individual or portions of WHAs, but had not been done for any in the Cascades
study area. Version 1 (FREP 2005) suggested that sampling should be in the lower part of the core
reaches of the WHA in an alluvial section. Any effects of upstream influences of timber harvesting or
road construction should be manifested in these downstream reaches so that these would be the best
place to monitor on a permanent basis.
The “best” length of stream to monitor on a permanent basis is unknown. Tailed frog adults
tend to have very small ranges with mean “neighbourhood” sizes (plus and minus 2 standard deviations
of distance moved between captures within one summer) of 97 m for breeding males and 105 m for
breeding females that were 8 years old or older (Daugherty and Sheldon 1982). Therefore 100-m should
be a minimum reach to be considered for permanent monitoring. Generally adequate stream reaches for
sampling stream morphology are considered to be 20-30 times the bankful width to provide consistent
results. This reach length would be about 100-150 m for an average 5-m wide stream that is occupied
by tailed frogs and included in a WHA. Reaches longer than the minimum would probably be better for
long-term monitoring because of the generally high natural variability of larval amphibian populations.
Particular study questions and how they were addressed to determine the most efficient sampling
schemes were:
1. Is there an “ideal” sampling scheme to determine tadpole population size for short (100 m) reach
lengths within a WHA?
a. Comparison of precision and accuracy of constant sampling effort (numbers of m sampled)
using combinations of segment length and sample size (1-m x 30, 3-m x 10 and 5-m x 6).
2. How do estimates of coefficient of variation vary by sample segment length and by population size?
a. Correlation of population size as independent variable with coefficient of variation as
dependent variable for different sample segment lengths.
b. Compare coefficients of variation of 1 m, 2 m, 3 m, 4 m and 5 m sample segment lengths
using nested samples.
TAILED FROG WHA METHODS 2005 DRAFT
9
OKANAGAN WILDLIFE CONSULTING
3. Is there an “ideal”reach length to sample to determine tadpole population density (number per 100m)? For example, with a constant amount of effort, would it be better to sample 100-m intensively,
or 300-m less intensively?
a. Compare nested reach lengths of 100, 200 and 300 m sampled with 5-m sample segments
for precision and accuracy as sample size and sampling intensity increases.
4. What is the natural variability of the sampling schemes within and between years on the same sites?
a. Use results from repeat visits to estimate within-year variability (i.e., when population size is
assumed to be unchanged) which we assume will estimate the lowest bounds on betweenyear variability due to sampling methodology, and
b. Reanalyze John Richardson’s multi-year tailed frog tadpole data (as cited in Maxcy 2003)
from Chilliwack River drainage to estimate between-year variability compared to within-year
variability.
5. How can size and/or age class distribution of tailed frogs be interpreted and used to monitor
populations?
a. Tabulate observed tadpole size class distributions to derive age class distributions for each
WHA.
b. Tabulate observations of tailed frog adults to determine the usefulness of adult observations
during in-stream searches for WHA monitoring.
Field Methods
Area-constrained searches were used to count tailed frog tadpoles. Search areas were the entire
width of the stream for a specified stream length measured at the stream centerline. These distances
will not exactly coincide with stream distances measured along TRIM GIS streamlines since those lines do
not include small-scale meanders in the streams. We kept track of total time spent sampling and total
numbers of m searched per day. Bankfull and wet stream widths were measured at the downstream
end of every 5-m sample segment.
In this project, all search areas were at least 1 m of stream length. For sample search areas of
3-m or 5-m, the search area was marked off in m so that the exact m in which a tadpole or adult was
first seen could be recorded. Every rock or log in the search area big enough for a tadpole to hide under
(>32 mm), and that was not embedded in fine materials, and that could be moved or lifted, was
searched on the underside for tailed frog tadpoles. The rocks were then replaced just downstream of the
immediate portion of the site being searched (which means they were often just moved 20-30 cm).
Large rocks and logs that could not be moved were searched (if possible) by hand combing the underside
to dislodge any tadpoles present. Where there were numerous rocks to be lifted, they were placed out of
the stream, or in an area already searched so that we could continue to lift remaining rocks. Coarse
gravels (16-32 mm) were hand raked to dislodge any tadpoles that might be hiding within the matrix. An
attempt was made to capture every tadpole and adult seen using dipnets or turkey basters (with the
opening enlarged so tadpoles would fit) so that total length (TL) for each tadpole, or snout-vent length
(SVL) for each adult, could be measured. Tadpoles were placed in containers filled with stream water on
the streambank. After a 5-m segment was sampled, the tadpoles and adults were measured, and
TAILED FROG WHA METHODS 2005 DRAFT
10
OKANAGAN WILDLIFE CONSULTING
released into the same place where they had been captured after any rocks removed from the stream
had been replaced.
Not every tadpole seen could be captured since some would escape under large rocks or logs, or
into pools deeper than 0.5 m which could not be efficiently searched. Brita water filters were used as
viewers to cut surface glare and to see through riffled surfaces. This meant one hand was on the filter,
one hand was lifting rocks, and there was no third hand available for catching tadpoles. If a rock
required a two-hand lift, then the filter was put down, but there was still no third hand available for
catching tadpoles. Tadpoles often would cling to the bottom of the rock until they could be swept off into
a container, but as many as 12 tadpoles could be found under a single rock, and not all would necessarily
cling to the rock until they could be picked off and put into containers All tadpoles that were noticed
escaping were counted in the total tally, but no measurements were kept (even though they were often
seen well enough to estimate the size class).
A 5-mm mesh net at the downstream end of the 5-m sample segments was used for only 2 of
the 15 field days. on those 2 days. Within the 23 segments sampled on those 2 days only 5 tadpoles
were found in the nets. 49 tadpoles were captured and 39 were seen but not captured. Only 2 of the 5
tadpoles were not accounted for within the segments, i.e., they were not seen within the segments, but
the other 3 were probably ones seen but which had escaped capture. We did not continue with use of
the downstream nets (which required considerable additional effort to set up at each segment,
particularly if there were overhanging shrubs and large cobbles and boulders) because very few escaped
tadpoles ended up in the nets (3 of 39), and there were very few which had ended up in the nets but had
not been seen (2 compared to 88 seen or captured). If we wanted to be sure to catch and count every
tadpole within a segment, then a downstream net should be used, and every moveable object in the
streambed should be moved out of the streambed. This would give an absolute abundance measure, or
be as close as possible to it as one could achieve. I felt we probably came within a few percentage
points of absolute counts, but this would be difficult to prove without much additional effort.
On repeat visits to a site, if at least 50 tadpoles had already been measured to develop a tadpole
size-class distribution during a previous visit, no further animals were measured for length. If less than
50 tadpoles were measured on the first visit, then measurements were made on the second visit, and the
measurements from the first visit not used to develop the size class distribution because of probable
double-counting of tadpoles.
TAILED FROG WHA METHODS 2005 DRAFT
11
OKANAGAN WILDLIFE CONSULTING
Study Design applied to the WHAs
WHA and Reach Selection
The study plan was initially to sample 8 WHAs selected at random from the 15 WHAs in the
Merritt TSA. Based on initial data collected during time-constrained searches from 2000-2002 surveys
WHAs were assigned bankful-width size classes of small (<3.5 m), medium (3.0-5-5 m) and large (> 5m). Three WHAs were selected from the first two size classes, and two from the third. Four of these
WHAs were selected (based on the WHAs with easiest access) for two extra repeat visits each at oneweek intervals to determine within-year variability. This study plan would require 16 field days.
All reaches selected for sampling on WHAs were pre-selected before field visitation. In the
absence of any other reason for selecting a site (principally length and difficulty of access, but also the
existence of some previous knowledge of the site as likely to contain tadpoles based on initial sampling
from 2000-2002), a reach starting 100 m upstream of the downstream end of the WHA was selected.
Sampling was always conducted proceeding in an upstream direction. The sampling area was termed the
monitored reach.
The final study design was changed somewhat from the initial plan, using 15 field days between
September 19 and October 7, 2005. Two of the WHA reaches selected were actually headwater frontier
reaches and one was a downstream transient reach, all with tadpole numbers too low to provide any
meaningful data for this monitoring. The tadpole numbers were lower than from the initial
reconnaissance-level surveys that provided the data upon which the WHAs had been selected, indicating
the highly variable numbers in these reaches, and that they are probably not suitable as permanent
monitoring sites. For the transient reach, the possibility of it being a transient reach had been
considered based on low gradient so that a site further upstream had been pre-selected as an alternate
sampling site. An additional WHA was substituted for one of the frontier reaches. An additional site
was selected on one other WHA that was already being sampled as a substitute for the other frontier
reach.
Sample Site Selection within Monitored Reaches
Within monitored reaches, all samples were randomly selected beforehand using random
numbers generated in Excel XP. The exception was the first 5-m segment in a monitored reach, which
was always sampled in addition to the random selection of 3 sample sites in the first hundred meters, but
was not truly randomly selected. In one case, we were in the field and had to generate a new random
number set, and did so by making a complete set of possible segments to be sampled on pieces of paper,
and literally pulled the numbers out of a hat. Sites were randomly selected without replacement, i.e.,
selected possible segments were not replaced into the sampling pool to be available again for sampling
within the same sampling session.
Version 1 (FREP 2005) suggests that sampling within a reach be at regular intervals. At the risk
of being didactic and patronizing, I must stress that these must be randomly selected. If the samples are
not randomly selected, then the Central Limit Theorem cannot be assumed to apply, the mean cannot be
assumed to be normally distributed and basic statistical tests cannot be assumed to be applicable.
Whatever the actual tailed frog tadpole microhabitat distribution may be within the reach does not
TAILED FROG WHA METHODS 2005 DRAFT
12
OKANAGAN WILDLIFE CONSULTING
matter, i.e., they do not need to be assumed to be clumped, regular, randomly or otherwise distributed,
as long as the sampling is done randomly. If only the first sample is randomly located, and the rest are
placed at some constant interval upstream, then there is only one sample (N = 1, i.e., the entire
monitored reach) since not all possible samples within the reach have an equal probability of being
sampled once the first choice is made. Samples must be randomly, and not regularly, located, within the
monitored reach if we wish to compare the reach to itself at a later date, or to another reach within the
same year.
If the samples are not randomly selected, then we could use the total or average number found
in the reach as one sample among a population of reaches (which would have a grand mean which would
be normally distributed if the reaches had been randomly selected), but we could not use the data for
comparisons of this reach to itself at a later date, or to other reaches. For example, if we were interested
in estimating the population of a complete WHA of 3000-m length, we could sample, say 6 100-m
reaches that were selected randomly, and then sample at regular intervals within each 100-m reach. The
estimated population for the entire WHA would have a mean that would be normally distributed and we
could compare the estimated population of the entire WHA to itself at a later data by taking another
random sample of reaches. But we could not compare individual reaches within the WHA to each other
using standard statistical tests because we cannot make any assumptions about the distribution of the
mean for each individual reach.
The initial study design was to estimate the number of tailed frog tadpoles in a 300-m monitored
reach in any given WHA by sampling with 10 5-m samples (termed the A samples). The first sample was
at meter 0 of the monitored reach (starting at the downstream end). Three additional 5-m samples were
selected at random from each of the 100-m sections (termed subreaches 1, 2 and 3 from the
downstream end) for a stratified design. Estimated numbers in each 100-m subreach could be estimated
and compared statistically within the monitored reach. In each 5-m sample, numbers of tadpoles and
adults were tallied to the m so that results could be analyzed separately for nested 1-m, 2-m, 3-m 4-m
and 5-m samples to derive and compare variability and accuracy between samples of different lengths.
When we began the study, it was not clear how much sampling we would be able to complete in
a day. In the event that we were able to cover more sampling than just the basic A sample (10 x 5-m
over a 300-m reach), we randomly selected 3 additional 5-m B samples from each 100-m subreach, and
3 additional 5-m C samples from each 100-m subreach, for a potential of 28 5-m samples within a 300-m
reach. We always sampled in an upstream direction, so that we did not cover B, C or other samples
opportunistically after sampling the A samples, but only sampled them as part of the planned day’s
sampling. At the beginning of the day, all planned A, B and C samples were measured out along stream
centerline using tapes or hip chain, and the downstream end of each sample site marked with flagging at
the stream edge. If hip chain was used, all topofil was gathered for later disposal.
During the first week of sampling, it became clear that the coefficient of variation decreased
predictably in every sample as sample size increased from 1 to 5 m, but that this would not answer the
question of how equivalent sampling intensity (e.g. 30-m sampled out of 100) sampled by different
sample lengths might differ. A simple trial of sampling a 100-m subreach by 3 randomly selected 5-m
and 15 1-m samples at the same time was undertaken. This quick trial showed that the population
estimates from sampling 15 total meters in with different sample lengths were not necessarily identical
TAILED FROG WHA METHODS 2005 DRAFT
13
OKANAGAN WILDLIFE CONSULTING
but could vary greatly in both estimated population, and in standard error of the estimate. Therefore for
the second week, 10 3-m samples (termed the D samples), and 30 1-m samples (termed the E samples),
were selected randomly from subreach 2 as additional sampling to compare to the 5-m A, B and
sometimes C sampling in the same subreach. The locations of D and E samples were not marked out by
flagging, but their locations were measured by steel or fiberglass tape from the nearest A, B or C sample
flag.
The 5-m (A, B, and sometimes C), 3-m (D) and 5-m (E) samples were selected independently
with replacement, i.e., meters sampled in the 1-m (E) sample were also available to be sampled in the 5m (A, B, or C), and 3-m (D) sampling. However, the samples were taken at the very same time always
proceeding in an upstream direction. This means there was some overlap between the samples since
they had each been randomly selected independent of each other. For example, a single given meter
was only sampled for tadpoles once, but might be considered part of both an A and E sample depending
on the random selection. Therefore, because of overlapping samples, there were only between 62 and
72 m of the subreach actually sampled even though technically there were 3 30-m lengths sampled
within the subreach. Because of this more intensive sampling undertaken beginning in the second week
of sampling, three of the monitored reaches were not a full 300-m in length because of time limitations:
two were 200-m in length, and one was just 100-m.
A one-year study would not be able to predict inter-year variability, but inter-year variability on a
given reach would not be lower than within-year variability. Therefore 4 sites were chosen for multi-visit
sampling. Since the area-constrained searches do considerable rearranging of the streambed, there was
a distinct possibility that the method itself would influence further sampling at the same sites. Therefore
when sites were resampled at the exact same samples as the previous samples, additional randomly
selected sites (usually the B and C samples) were sampled. Two of the sites were not visited a third time
because it seemed to become clear in the field that the sampling was influencing the population. The
final sampling WHAs, dates, and samples made are listed in Table 1.
Analyses
Tadpole numbers were estimated as population number per 100-m stream length. Tadpole
density per m2 of stream is the usual statistic compared in other published studies on tailed frog tadpoles,
and was recommended in Maxcy (2003) and Version 1 (FREP 2005). However, while density may be a
convenient measure to compare a number of streams to each other, it will not be appropriate for
comparing a stream to itself at a later date. Tadpole density per m2 will vary with stream wet width
which may vary daily and throughout the season. Therefore the statistic may vary when the population
has not really changed in size.
For example, after a heavy rainfall on September 29, 2005, the water level in the stream on
which we were working rose by several cm over the course of the day, and in the one spot measured
that day, wet width was 1.5 times wider than when measured the previous week. Density per unit
stream area would have changed without the actual population being any different from the previous
week. Water level remained high when the site was checked the next week, and channels that were dry
the first week, contained tailed frog tadpoles the third week. Therefore density really did change over
the 3-week sampling period (tadpoles were using the entire wet width), though the tadpole numbers per
TAILED FROG WHA METHODS 2005 DRAFT
14
OKANAGAN WILDLIFE CONSULTING
100-m stream length probably did not change at all except through whatever mortality may have
occurred over that period (and assuming that any emigration out of the monitored reach over the sample
period would be balanced by immigration).
Even when comparing a number of streams of different widths to each other, density can only be
used as a valid measure if the ratio between stream width and tadpole numbers is linear and the yintercept is 0 (in which case the value of the ratio is the slope of the regression line). Any relationship
between these two variables that is not linear would confound the use of density as a valid measure and
analysis of covariance should be used to relate the two variables.
For these analyses, all population estimates are presented as numbers of tadpoles estimated per
100-m stream length. This was used because it represents a real number of animals over a typical
monitored reach, and gives a real idea of population size, although numbers per linear stream meter
could just as well have been used. For each case, the number of samples used to calculate the estimate,
the sample segment lengths used, and the sampled length from which samples were drawn are given.
Coefficient of variation (CV; standard deviation divided by the mean) is expressed as a percentage of the
population estimate. Precision is expressed as the standard error of the mean (SE; standard deviation
divided by the square root of the sample size) in the same units as the mean (population estimate) and
as percentages of the mean (population estimate).
Since the actual population size was not known, the accuracy of any sample cannot be absolutely
known. Here I have used as a measure of accuracy the absolute and the percent difference between the
population estimate for any given sample and the final population estimate for that same reach (or subreach) using the most complete data set possible within this project for that reach (or sub-reach). Only
on one sub-reach did we sample an entire 100-m subreach so that accuracy would be known since the
actual sample-able population size would have been known. All samples could then be compared to the
complete reach. However, this was on the second visit to that site, and there appeared to be a
significant reduction of the population in the segments that had been sampled on the first visit which may
have confounded statistical comparisons. Sampling entire 100-m segments s would have also allowed
accuracy to be estimated precisely since the actual population size (or at least every tadpole that was
available to be sampled and was not under immovable rocks or logs) would have been known.
Field data was entered into an Excel spreadsheet each evening. The data was analyzed after the
first week, and then entered and analyzed daily after that. All raw data, as well as preliminary analyses
and UTM locations of starting points for monitored reaches, are contained in the Excel file named ASTR
2005 Field and Analysis Data.xls. The entire data set cannot be repeated in this document, but the
reader who has any questions about the analyses performed here and the data from which it was drawn,
is encouraged to obtain a copy of this file to check the analyses while reading this report, or to perform
additional analyses that may not have been undertaken within this report.
RESULTS and ANALYSES
A total of 1735 tailed frog tadpoles and 98 adults were counted in the 15 field days (Table 1). An
average 18.8 m of stream length were sampled in one hour by a team of two (Table 1). Hours sampling
in Table 1 only consider actual time spent sampling, and not time spent collecting other data, time spent
TAILED FROG WHA METHODS 2005 DRAFT
15
OKANAGAN WILDLIFE CONSULTING
marking out sampling points on the stream, or time getting to and from the sites by vehicle and on foot.
Meters sampled per hour varied considerably from 11 to 30 based on width of stream, depth of stream,
complexity of stream bed (principally numbers of cobbles and boulders), and the numbers of tadpoles
that had to be caught and measured. The single stream where an entire 300-m was searched in 1.5
hours was largely dry (11 of 20 points where width was measured were dry), and the few pools with
water could be quickly searched.
Not all tadpoles could be caught in the sampling areas. On average, 24% of tadpoles were not
actually caught, but swam away and were tallied but not measured. We tried to avoid any double
counting by continually working upstream, and letting tadpoles escape only if they were swimming
towards an area that was already counted. If they were swimming towards an area that had not yet
been counted, then every effort was made to capture them, or at least watch to where they swam so
they would not be double counted. Very few tadpoles (5 of 39 that were seen but not captured) ended
up in the nets set downstream on 2 of the sampling days, so tadpoles that were dislodged did generally
probably not move more than a few meters, but generally were swept downstream. In relatively slowmoving, shallow and simple streams, <20% of tadpoles escaped, but in faster, deeper and more complex
streams, up to 46% of tadpoles were not caught. The extra time spent to try and capture these tadpoles
was not considered to be well spent since the rocks downstream of them had already been moved once
(but had not removed from the stream as has been done in some studies), and there were therefore too
many downstream crevices for them to hide in. The capture success could probably be raised if all rocks
were removed from the stream to be replaced after sampling, but the sampling would have been
considerably slower in that case, and not all large rocks could ever be removed in many cases.
True population size can never been known with single sample methods since in a given reach
there will almost always be some boulders and logs that cannot be moved, and usually some pools
deeper than 0.5 m that cannot be searched completely. The number that may have entirely escaped
notice was thought to be fairly low given the intensive “rubble-rousing” search methods, and the counts
given here were thought to be within a few percentage points of actual numbers. Mark-recapture
sampling would be required to confirm actual efficiency of the method as a complete census.
Comparison of Sampling Schemes with 30% Intensity
For 30% intensity sampling (30-m sampled out of 100-m reach), segment lengths of 1-m (n=30), 3m (n=10) and 5-m (n=6) performed equally well in accuracy but not in precision at estimating tailed frog
population size in the 100-m reach except in certain situations (Table 2). Accuracy was determined by
comparison to the best estimate for the reach based on all the m sampled within the reach (Table 2).
Accuracy was the absolute difference of the estimated population from the best estimate in the same units
TAILED FROG WHA METHODS 2005 DRAFT
16
OKANAGAN WILDLIFE CONSULTING
Table 1. Wildlife Habitat Areas (WHA) sampled for Coastal Tailed Frogs in the Merritt Timber Supply
Area, east side of Cascade Range, British Columbia, 2005.
WHA1
Date
Bankfull
Width
(m)
Wet Monitored
Width
Reach
(m) Length (m)
Samples2
Total m
Hours
sampled Sampling
m/hour
N
N
sampled Tadpoles3 Adults3
3-004L
3-004U
Oct 7
Oct 7
4.9
4.7
2.4
2.7
200
100
ABC
AB
80
35
3
1.5
26.7
23.3
1
35
0
0
3-014
Oct 6
2.7
1.7
200
ABDE
94
5
18.8
117
0
3-016S
Sept 28
4.2
2.6
200
ABDE
97
7.5
12.9
218
11
3-017U
Sept 23
Oct 3
5.7
-
3.3
-
300
300
A
A(B)DE
50
97
4
6
12.5
16.2
87
133
1
1
3-017L
Sept 27
Oct 4
5.9
2.6
100
100
ABDE
Entire
67
100
4
3.5
16.8
28.6
114
83
6
2
8-011
Sept 19
Sept 26
Oct 2
2.9
-
1.9
-
300
300
300
A
ABCDE
A
50
167
50
2.25
6
2.25
22.2
27.8
22.2
17
94
9
2
22
2
8-012
Sept 20
3.2
2.3
300
AB
95
5.75
16.5
66
1
8-078
Sept 27
5.7
0.4
300
Entire
(300)
(1.5)
(200.0)
1
1
8-080
Sept 22
Sept 29
Oct 5
4.9
-
1.9
-
300
300
300
A(E)
A(BC)DE
A(BC)
62
107
110
5.75
7.5
6
11.3
14.3
18.3
212
304
243
7
16
17
8-082
Sept 21
2.4
0.8
300
ABC
140
4.75
29.5
1
9
41401
474.75
18.8
1735
98
Totals
1
Identified by their prov. reference number; L = Lower site; U = Upper site; S = South arm of WHA
A, B, C = 5-m samples at the rate of 3 samples each per 100-m; D = 10 x 3-m samples and E = 30 x 1m samples only within one 100-m subreach. Bracketed samples were not done over entire
monitored reach because of time constraints.
3
Totals for each sampling day are absolute total counted, discounting D and E Sample overlap.
4
Total does not include 8-078 because most of reach was dry.
2
as the estimate, and as a percentage of the best estimate. Possible high or low bias was estimated using
the signed difference (positive or negative) of the sample estimate from the best estimate both in the
same units, and as a percentage of the Precision was estimated by determining the CV (which does not
vary with sample size once an adequate sample size is achieved to determine it reliably) and the SE both
in the same units as the mean, and as a percentage of the mean (Table 3). Average accuracy and
precision were calculated for the data set with the three anomalous situations referred to below included
(N = 6), and then, for comparison, without them included (N = 5).
TAILED FROG WHA METHODS 2005 DRAFT
17
OKANAGAN WILDLIFE CONSULTING
Table 2 . Accuracy and bias of sample estimates compared to best available population estimates in 6
100-m reaches in Cascades Tailed Frog WHAs sampled at constant 30% intensity by 1-m, 3-m
and 5-m sample segment lengths for tailed frog tadpoles, 2005.
WHA
N
Total m
sampled
3-014
3-016
3-017L
3-017U
8-011
8-080
64
62
67
62
72
72
N
Tadpoles
Counted
Best Population
Estimate in 100m reach
78
127
110
92
37
211
Sample Population Estimate
in 100-m reach
30 x 1-m
122
205
164
148
51
293
97
227
190
147
27
10 x 3-m
6 x 5-m
150
172
130
227
207
270
152
123
57
280
Mean Difference of (Sample Estimate. - Best Estimate)
Not including anomalous (grey) samples
-4.5
-0.5
-8.3
-3.4
14.9
9.4
Mean Difference of (Sample Est – Best Est) as % of Best Est.
Not including anomalous (grey) samples
-8.6
-0.7
-1.9
0.9
4.9
0.6
Mean Absolute Difference of (Sample Estimate. - Best Estimate)
Not including anomalous (grey) samples
20.4
19.5
19.4
16.8
20.4
16.0
Mean Absolute Difference (Sample Est – Best Est) as % of Best Est.
Not including anomalous (grey) samples
13.4
11.2
13.0
12.4
17.4
10.9
143
40
327
Bias
Accuracy
Table 3. Precision of sample estimates estimated by Coefficients of Variation and Standard Errors in 6
100-m reaches in Cascades Tailed Frog WHAs sampled at constant 30% intensity by 1-m, 3-m
and 5-m sample segment lengths for tailed frog tadpoles, 2005.
Coefficient of
Variation (%)
WHA
3-014
3-016
3-017L
3-017U
8-011
8-080
Standard Error
(tadpoles/100 m)
Standard Error as %
of Sample Estimate
30 x
1-m
10 x
3-m
6x
5-m
30 x
1-m
10 x
3-m
6x
5-m
30 x
1-m
10 x
3-m
6x
5-m
142
79
150
89
195
88
65
43
42
111
25
33
52
24
10
42
46
23
39
94
26
14
27
16
36
28
27
18
17
46
108
104
92
152
69
Mean
127
95
Not incl. grey samples
Range
114
101
53
53
36
27
61
62
33
43
52
37
47
48
84
46
20
35
29
48
22
43
231
311
251
33
212
14-27
322
22-48
212
17-34
28
14
61
20
34
19
1
ANOVA comparison of SE %, F(2,15)=1.11; p=0.35 2ANOVA comparison of SE% F(2,12) = 3.45, p = 0.06
TAILED FROG WHA METHODS 2005 DRAFT
18
OKANAGAN WILDLIFE CONSULTING
The 1-m segment sampling performed very poorly on the site with the lowest estimated population (8-011).
Even though the sample had a low SE, the estimate was the least accurate. When tadpole populations are
low (<100 per 100-m reach), sampling with 1-m segments should be more intensive (higher N) to maintain
the accuracy as well as precision. With only one trial on low density sites, I am not sure if this is a general
characteristic of 1-m segments. However, it might be a general characteristic since the initial 15% intensity
trial (3 x 5-m segments and 15 x 1-m segments) on WHA 8-080 in the first week of the study also had high
precision, but very poor accuracy. Compared to a 5-m concurrent sample, the 1-m segment sample was
much better in precision (SE 14% vs 27%) but much poorer in accuracy (population estimate 547 vs 247
compared to best estimate of 242 based on 50% sample 2 weeks later). Sampling with 1-m segments at
lower intensities than 30% can clearly result in poor results even in dense populations, whereas 5-m
segments appeared to have relatively good accuracy and precision even with the minimum number of
samples (n = 3, or 15% intensity) to calculate precision (see next two sections).
The 5-m segments performed very poorly in the one reach (3-017 Lower) that had large amounts of
unoccupied habitat within it and tadpole distribution was very patchy. This site had 3 sections of bedrock
cascades from 10 to 15-m long that were not occupied by tailed frog tadpoles. The site should not have
been used for monitoring according to the Version 1 recommendations (FREP 2005) since it was not an
alluvial reach, but the site was chosen because it was 100-m above the downstream end of the WHA, and
once we were at the site it was already noon (we had sampled the frontier reach 8-078 in the morning very
quickly and without any usable results) and there was not time to spend finding another suitable site. So it
was used anyway as a contrasting situation to the other reaches just to see how the results might differ.
This was the only reach sampled in 2005 that had significant amounts of clearly distinguishable non-used
habitat within the reach. For sites like this, many smaller segments (1-m or 3-m) performed better in a
simple random sample than did the fewer longer 5-m segments. An alternative to simple random sampling
would have been stratifying the reach after initial sampling, but it would also be easier to just choose reaches
that are alluvial and uniform in habitat, and reject ones for long-term sampling that require within-reach
habitat stratification.
The 3-m segment performed poorly on one site (3-016) only because of a transcription error on the
field sheets made before sampling, i.e., not because of any inherent property of 3-m segments. Only 6 of
the planned 3-m 10 samples were actually taken for the full 3-m and the others were only sampled for the
first m only. Once the error was realized, we could not go back and sample these sites since sampling had to
proceed in an upstream direction and trying to resample partially sampled sites may sample tadpoles that
were initially somewhere else before being caught and released. (Upon release they would often be seen
swimming several meters.) These 1-m samples were not counted as part of the 30 1-m samples. It would
not be valid within this planned comparison to simply draw several meters at random out of the many meters
sampled within the reach to fill in the missing sampling.
Not including the anomalous samples cited in the previous three paragrapsh, there was <1% bias in
the mean sample estimates compared to the best estimates (Table 2). Therefore, segment length did not
appear to bias the sample estimate either upward or downward on average. Average accuracy of the sample
estimates was in a very narrow range between 10.9 and 12.4 % of the best estimate, as long as the
anomalous samples were not included (Table 2). Therefore, segment length did not appear to influence the
average accuracy of the sampling, but the best average accuracy that could be achieved was only 10-12% at
TAILED FROG WHA METHODS 2005 DRAFT
19
OKANAGAN WILDLIFE CONSULTING
30% sampling intensity by any of these segment lengths.
Precision (SE in %) of the 3-m segment sample was 1.5 times that of the 1-m and 5-m segments on
average (p=0.06, Table 3). I do not know what particular property of 3-m segments might have lead to this
result but the precision did not appear to be as good as the 1- and 5-m segments, even though accuracy
was similar and there was no apparent bias.
To determine if this poor accuracy and precision of short segments were a general feature of lower
intensity sampling, the same data set of 6 WHAs was reordered randomly and accuracy and precision
calculated as sample size was increased within these samples. The mean accuracy and precision of 6
random trials for the 6 WHAs are presented (Figure 2) but not including the anomalous trials as previously
discussed. These are not independently randomly selected from the entire population each time, but are
selected only from the initial random sample so that the results really only tell us how this one sample set
performs when sampled partially so that we can see how the set performs at sampling intensities lower than
30%.
The 5-m segment performed best for both accuracy (Figure 2 top) and precision (CV, Figure 2,
middle). As few as 3 samples (15 m sampled) resulted in estimates within 5% of the final estimate. 1-m
segments were similar to the 5-m segments in precision, with the CV estimated within 5% with as few as 12
m sampled but accuracy was not within 5% of final estimate until 21 m had been sampled. The 3-m
segments did not reach 5% of the final accuracy until 8 segments (24 m) had been sampled, and reach 5%
of final precision until 7 segments (21 m) had been sampled. SE of the 1- and 5-m segments were
equivalent to each other, but the SE of the 3-m segments was 10% higher than either the 1- or 5-m
segments, and this did not change with sample size (Figure 3 bottom).
Based on these trials (n=5), 3-m segments appeared to be a “neither here nor there” segment
length for sampling tailed frog tadpoles. 1-m segments had a large number of zero-result segments, but the
SE was equivalent to the 5-m segments because SE is calculated with the higher sample size taken into
account. 5-m segments are long enough that almost all segments have larger numbers of tadpoles. 3-m
segments may have been short enough to contain larger numbers of zero-result segments, but long enough
that clumps of tadpoles would have been sampled thoroughly resulting in some very high result segments.
When SE was calculated, the relatively high CV of 3-m segments compared to 5-m segments was not offset
by the increase in sample size from 6 to 10, and while CV decreased from 1-m to 3-m segments, the
decrease was not large enough to be offset in the decrease in sample size from 30 to 10. While it would be
tempting to conclude that the particular clumped nature of tadpole distribution in these streams was such
that both 1-m and 5-m segments performed equivalently in most situations but that 3-m segments
performed relatively poorly in precision, although accuracy was not different. I do not think that this is a
general property of 3-m segments compared to tailed frog distributions because it would be hard to imagine
how this could be so, since samples were all randomly selected, and the same sort of low precision did not
show up in the nested sampling (see next sections).
TAILED FROG WHA METHODS 2005 DRAFT
20
OKANAGAN WILDLIFE CONSULTING
Mean Absolute Difference as %
(Sample Est. - Best Pop Est.)/Best Est.
80
70
60
50
40
30
20
10
0
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
140
130
120
CV %
110
100
90
80
70
60
50
40
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Std Error as % of Mean
50
45
40
35
30
25
20
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
N M et er s Samp l ed
1-m
3-m
5-m
Figure 2. Accuracy (top graph, as absolute difference of sample estimate from best estimate as % of
best estimate), and precision (middle graph, Coefficient of Variation as %; bottom graph,
Standard Error as % of sample mean) estimated from 6 randomly selected trials of 100-m
reaches dataset as sampled using 1-m, 3-m and 5-m sample segments in 6 Coastal Tailed Frog
WHAs on the east slopes of the Cascade Ranges, B.C., Sept-Oct, 2005.
TAILED FROG WHA METHODS 2005 DRAFT
21
OKANAGAN WILDLIFE CONSULTING
Table 4. Mean, minimum and maximum of Coefficients of Variation for estimated tailed frog tadpole
populations per 100-m stream length calculated based on 10 samples over 300-m stream lengths (5 to
15% sampling effort), east slope Cascade Ranges, B.C., 2005.
Subsample Segment
Length (m)
Coefficient of Variation (%)
Mean
Min
Max
Standard Error
(% of Mean)
Mean
Min
Max
N = 6 trials in 4 WHAs with estimated tadpole populations >100/100-m stream length
1
102
86
121
32
27
38
2
71
53
97
22
17
31
3
58
39
75
18
12
24
4
53
43
73
17
14
23
5
42
31
57
13
10
18
N = 4 trials in 2 WHAs with estimated tadpole populations <100/100-m stream length
1
186
118
242
59
37
76
2
156
102
211
49
32
67
3
138
96
179
44
30
57
4
129
76
179
41
24
57
5
128
86
169
41
27
54
Precision and Accuracy by Segment Length and Population Size
The CV varied with population size and with sample segment length for nested 1-m to 5-m samples
within 10 5-m sample segments randomly selected within either 200-m or 300-m reaches (Figure 3a). When
estimated tadpole populations were >100 per 100-m, then the CV was fairly predictable, occurring within
fairly narrow bounds (Table 4). The correlation between population size and CV was not linear, and was
proportional to an inverse function of the general form: y = 1/sqrt(population estimate). The particulars of
this correlation were not presented here.
Using the nested 3-m sample segments did not show the high CV of the comparison of 1-m , 3-m
and 5-m segments using constant effort, i.e., the samples that were independently selected and were not
nested. Therefore, it does not seem to be some innate characteristic of 3-m sample segments relative to
tailed frog distributions that dictates a relatively high CV compared to shorter or longer sample segments. SE
was not compared using this data because sample size was held constant, and SE is just a function of CV
divided by sample size so no additional information would have been added to the comparisons.
Accuracy of short 1-m to 3-m segments tended to be relatively poor (i.e. more variable) compared to
longer segments but this was expected given that shorter segments sampled fewer actual m because sample
size was held constant (Figure 3b). More importantly, bias of the shortest 1-m and 2-m segments was
tending to the high side (Figure 3b). Of 10 1-m trials, only 1 was negative (-22%), three were near zero,
and 6 were >18% above zero, for an average upwards bias of 28%. Average upwards bias of 2-m
segments was 20%. Bias was not evident in the 3-m segment lengths. This bias resulted because there
were proportionately more tadpoles seen in the first 2-m of the segment than in the last 3-m (m by m totals
TAILED FROG WHA METHODS 2005 DRAFT
22
OKANAGAN WILDLIFE CONSULTING
were 166, 217, 78, 142, 132).
Short 1-m and 2-m segments tended to have upward bias on population estimates when part of the
5-m segments but this was not apparent when examining the 1-m segments that were sampled
independently of the 5-m segments (previous sections). Using very short sample segments requires many
boundary decisions as to whether tadpoles and rocks were in or out of the short sample. There may be
some tadpole movements within the sampling session because disturbed tadpoles that move will tend to be
seen, and they will tend to be swept downstream. This uneven sampling of 5-m segments probably means
that the nested sample results were somehow biased simply by the way they were collected, and we might
give more weight to the results from the 1-m vs 3-m vs 5-m sampling than this nested sample set for
comparisons of sample segment lengths.
Coefficient of Variation (%)
300
8-011 24 3rd Visit
250
8-011 38 2nd Visit
8-011 38 1st Visit
200
8-012 63
3-014 142
150
3-017U 169
8-080 206 3rd Visit
100
3-016 221
8-080 344 1st Visit
50
8-080 373 2nd Visit
0
1
2
3
4
5
Nested Sample Segment Length (m)
Difference (%) from final
(5-m) Population Estimate
140
120
8-011 24 3rd Visit
100
8-011 38 Second Visit
8-011 38 First Visit
80
8-012 63
60
3-014 142
40
3-017U 169
8-080 206 3rd Visit
20
3-016 221
0
8-080 344 First Visit
8-080 373 Second Visit
-20
-40
1
2
3
4
5
Nested Sample Segment Length (m)
Figure 3. A)Coefficients of Variation (upper graph) and B)Accuracy and bias as percentage of final
estimate (lower graph) of tailed frog tadpole population estimates per 100-m stream length using
nested sample segment lengths from 1 to 5 m (n = 10 for each sample) for WHA stream reaches,
east slope Cascade Ranges, B.C., 2005. Population estimate of each WHA is in legend.
TAILED FROG WHA METHODS 2005 DRAFT
23
OKANAGAN WILDLIFE CONSULTING
Table 5. Tailed frog tadpole abundance compared among 100-m sub-reaches within longer reaches
using 5-m sample segments.
Date
Reach
Length
(m)
6-Oct
3-016S
Sub-reach Means1
Samples
Sampling
Intensity
1
2
3
d.f.
F
p
200
A
AB
15%
30%
-
5.3
6.2
7.3
6.5
1,4
1,10
0.64
0.05
0.47
0.83
28-Sep
200
A
AB
15%
30%
14.3
13.5
9.3
11.3
-
1,4
1,10
3.31
0.81
0.14
0.39
3-017U
23-Sep
3-Oct
300
300
A
A
15%
15%
8.7
4.7
11.7
5.0
7.3
6.0
2,6
2,6
7.39
0.22
0.02
0.81
8-011
19-Sep
300
A
15%
1.3
4.3
0
2,6
3.03
0.12
26-Sep
300
300
300
A
AB
ABC
15%
30%
45%
2.0
2.5
2.6
1.0
2.0
2.6
1.7
2.5
3.4
2,6
2,15
2,24
0.19
0.08
0.28
0.83
0.93
0.76
2-Oct
300
A
15%
2.3
0.7
0
2,6
2.29
0.18
8-012
20-Sep
300
A
AB
15%
30%
4.0
2.0
5.7
5.0
1.3
1.5
2,6
2,15
2.74
2.01
0.14
0.17
8-080
22-Sep
300
A
15%
12.3
18.3
12.0
2,6
1.57
0.28
29-Sep
300
A
15%
13.0
20.0
9.0
2,6
2.76
0.14
5-Oct
300
A
15%
6.3
13.3
6.0
2,6
7.84
0.02
200
200
200
A
AB
ABC
15%
30%
45%
6.3
11.3
11.2
-
6.0
10.7
9.0
1,4
1,10
1,16
0.02
0.02
0.52
0.90
0.88
0.48
WHA
3-014
1
Sub-reach means are raw numbers counted per 5-m segments (equivalent estimate per 100-m would be
these figures multiplied by 20).
Contrast of Monitored Reach Lengths
Do 100-m sub-reaches differ within longer reaches?
100-m sub-reaches were compared within longer 200 or 300-m reaches using ANOVA. First 15%
intensity sampling was examined in 6 reaches (3 x 5-m segments per 100-m), then 30% intensity sampling
for 5 reaches(6 x 5-m segments per 100-m), and finally 45% intensity sampling for 2 reaches (9 x 5-m
segments per 100-m). In only two cases (Table 5; 3-017U on the first visit, and 8-080 on only the third visit)
were single 100-m reaches significantly different from the longer reaches in which they were located at the
alpha = 0.05 level. The conclusion is that within relatively uniform alluvial reaches, estimated tadpole
populations generally do not differ from 100-m sub-reach to 100-m sub-reach.
I am not sure over what length of reach this may apply since we only looked at sub-reaches that
were adjacent to each other. This might not apply to randomly selected 100-m core reaches over the entire
length of a WHA. It was clear based on the entire set of WHA reaches sampled that this will not apply unless
TAILED FROG WHA METHODS 2005 DRAFT
24
OKANAGAN WILDLIFE CONSULTING
we delineate the core reaches based on pre-sampling or stream reach stratification, since frontier and
transient reaches occur within the WHAs and lack permanent populations of tadpoles.
Is anything gained by sampling reaches longer than 100 m?
If the goal is to monitor just one site, then we need to ask what length that site should be. Is 100 m
long enough to be a reliable reach to monitor on the long term? Will a slightly longer reach perform more
reliably in accuracy and precision than a shorter reach? Would a given amount of effort be better spent on
one short reach, one long reach, or multiple short reaches? How is accuracy or precision affected when
using a constant effort over 100-m, 200-m or 300-m?
In low density reaches (<100 tadpoles per 100 m), I compared precision and accuracy using
sampling efforts of 5% to 45% spread over 100 m, 200 m and 300-m (WHAs 8-011 up to 45% and 8-012
up to 30%) sampled with 5-m segments (and one could do the same analysis using the nested 1-m to 4-m
samples from the same data set). In high density reaches (>100 tadpoles per 100 m), I compared precision
and accuracy in sampling efforts of 5% to 30% over 100 and 200 m (WHAs 3-014 and 3-016). To estimate
accuracy, I determined the difference of the sample population estimate to the best estimate of the tadpole
population of the WHA using as much sampling as was available, including the 3-m and 1-m segment
samples for sites in which they were available (8-011, 3-014, 3-016). For the other site (8-012), the final
estimate using the maximum sampling was considered the best estimate, in which case accuracy could not
be judged, but precision could be judged. Only reaches which were not judged to be significantly different
from each other within a WHA (see previous section) were used in this analysis.
In high density WHAs, it did not matter how the sampling was done. Sample size was more
important in determining accuracy and precision than whether the samples were taken over 100 m or 200 m
reaches. It seemed that tadpole populations were numerous enough, and evenly distributed enough, that
the results did not vary with reach length over which the samples were taken. Final CVs of these 2 WHAs
from the 12 sample set were 33% and 40%. CV was fairly well predicted by as few as 3 samples (ranges of
25-43% and 38-47% respectively) which did not improve with an increase to 6 samples, (ranges of 26-42%
and 37-46% respectively) no matter whether they were sampled over the same 100-m reach, or the increase
in samples came by sampling the adjacent 100-m reach. SE with only 3 samples ranged between 14-27%
(average 22%) of the mean, with 6 samples ranged between 11-19% (average 16%) of the mean, and with
12 samples was 10-12% (average 11%) of the mean. Since SE is calculated with sample size, it is expected
to decrease as sample size increases.
In high density WHAs, the final accuracy of the 12 sample set was within 4% and 10% of the best
estimates in the 2 WHAs. Average accuracy given only 3 samples in a 100-m reach was 14% (range 7-20%)
and 19% (range 13-28%) respectively. This improved to average accuracies of 4% (range 1-6%) and 10%
(range 1-20%) with only 6 samples. It did not matter for accuracy whether the sample size was doubled by
increasing samples within the 100-m reach, or by sampling the adjacent reach.
In low density WHAs, the same held true but CV was larger (final estimates of 84-87%), and sample
sizes had to be much larger to achieve an equivalent SE to the high density WHAs. The range of estimation
of CV was quite large with samples sizes of only 3 (range 25-173), which progressively decreased as sample
size increased (n=6, CV range 45-138%, n=9, CV range 75-118). The mean SE with only 3 samples in 100
m was 53% in 8-012 and 62% in 8-012; with 6 samples (whether taken within one 100-m reach or over
TAILED FROG WHA METHODS 2005 DRAFT
25
OKANAGAN WILDLIFE CONSULTING
adjacent 100-m reaches) was 34% and 44% respectively, with 9 samples (whether taken within one 100-m
reach or over three adjacent 100-m reaches) was 32% and 34% respectively, with 18 samples (taken over a
300-m reach) was 20% and 24% respectively, and with 27 samples (taken over a 300-m reach) was 16% (in
8-011). How the samples were taken, i.e., by sampling a 100-m reach more intensively, or sampling the
adjacent 100-m reaches to increase sample size, did not affect the precision of the results.
In low density WHAs, final accuracy of the sample set was within 1% (8-011, n=27) and 6% (8-012,
n=18) of the best estimates in each WHA. Average accuracy given only 3 samples in a 100-m reach was
32% (range 5-90%) and 39% (range 15-52%) respectively. This improved to average accuracies of 20%
(range 7-47%) and 28% (range 1-57%) with 6 samples and to average accuracies of 20% (range 7-47%)
and 28% (range 1-57%). Average accuracy did not improve at all with increase of sample size to 9 and 12
samples. In 8-011, average accuracy did not improve until there was a step decrease to 12% (range 717%) when sample size was increased from 12 to 18. It did not matter for accuracy whether the sample
size was doubled by increasing samples within the 100-m reach, or by sampling the adjacent reach.
In low density stream reaches, the maximum possible number of samples is required to achieve
good accuracy within a reach, and precision with SE to within 10% of the mean will not be realistically
achievable. The best achievable SE in a low density stream reach is about 20% with 18 samples. 18 5-m
sample segments would mean sampling almost an entire 100-m stream reach, so, in low density streams,
large sample sizes with 5-m segments are realistically only achievable by sampling longer lengths of stream.
Since 1-m segments perform similarly to 5-m segments in terms of standard error for equivalent total lengths
sampled (see previous section), changing the sample segment length will not change the achievable SE (but
may affect bias—see previous sections).
Sample one long reach, or multiple smaller reaches?
With the same dataset, we can estimate the differences in precision (CV and SE) by sampling several
short 100-m reaches compared to grouping the data from long reaches by 100-m subreaches since the
samples were stratified so this would be possible. Differences in accuracy are not obtainable because the
samples were nested so that the grand mean of the small reaches will always equal the mean of the long
reach. This analysis tests whether it is better to use one long monitored reach with many samples within it,
or whether samples should be grouped by reach and treated as subsamples, and each reach treated as one
sample. For instance, how will the CV and SE of a 300-m reach sampled at 30% effort (90 m sampled, n=
18 5-m segments) compare to three 100-m reaches each sampled at 30% effort (90 m total sampled, n = 3
100-m reaches). This is equivalent to increasing the sample segment length to 100-m from 5-m, but the
100-m is subsampled to determine the mean for that sample, rather than completely sampled as for the 5-m
segments.
Sixteen comparisons were made in total (Table 6) at 6 WHA streams. There were general decreases
in CV, and a few very large decreases in CV at 30% sampling intensities (greyed cells in Table 6) that were
not as evident at 15% sampling intensities. For low density populations, there were no real gains in
precision (SE) by treating 100-m subreaches as separate sample segments (Table 6). For high density
populations, there was no gain in precision at the 15% sampling intensity, but there may have been a gain at
the 30% sampling intensity where SE dropped from 12% to 3% (Table 6). However, based on only 2 trials
this should not be taken as the general case.
TAILED FROG WHA METHODS 2005 DRAFT
26
OKANAGAN WILDLIFE CONSULTING
For reaches up to 300-m in length, we are no better off estimating tailed frog tadpole population
sizes by using many short sample segments within a long reach, or by using fewer long 100-m sample
segments. The results of this analysis might be applicable to power analyses to guide study design for
sampling multiple reaches to estimate populations in entire WHAs. If reaches are fairly uniform in stream
morphology and conditions, and tailed frog tadpole populations are similar throughout a WHA, then this data
might be useful for estimating power and sample sizes for estimating populations within entire WHAs, or at
least within uniform reaches. However, there will be limits to this application since we sampled 100-m
reaches that were adjacent to each other, rather than randomly selected 100-m reaches from anywhere in
the core reach of each WHA.
Within-site Variation Within the Year
Time-of-year Effect
The A sample (10 x 5-m segments over a 300-m reach) was sampled three times at 2 WHAs, and
twice at one WHA at intervals of at least one-week using exactly the same segments, i.e., not by a newly
selected random sample. The 30% x 3 sample (30 x 1-m, 10 x 3-m and 6 x 5-m over a 100-m subreach)
was sampled twice at one WHA. At some of the sites, additional random subsampling took place as a check
on the first sites to see if disturbance of the stream bed or handling of the tadpoles had some effect on their
local abundance in given segments.
At the first two resamples (from the third week of September to the fourth week of September),
there were no significant differences in estimated population size (ANOVA). However, when resampling all
three sites in the first week of October, all sites showed a reduction in population estimate in the A sample
(34, 34, 18; 296, 306, 194; 174, 112; 207, 67; the first week of October sample estimate in bold) that
was not reflected in the other random samples done in the first week of October in segments that had not
been previously disturbed or sampled within the same reaches. In each case, these previously unsampled
segments had higher population estimates in the same first week of October than the previously disturbed
sites (194 vs 242; 112 vs 160; 67 vs 140). In 3-017L, 111 tadpoles were counted in the last week of
September on only 67 m of the 100 m, but in the first week of October the entire 100-m was sampled, and
only 83 tadpoles could be found.
At the time (in the field), and based on initial tallies of the data (without performing any ANOVAs), I
concluded that there was an effect of the actual sampling that was disturbing the populations so that the
final visits were not sampling the same population. The results were not consistent, since there was no
apparent decline from the third to the fourth weeks of September, but sampling these sites again in the first
week of October showed a decline. This decline in the first week of October, when compared to previous
sampling, and compared to concurrent sampling on previously unsampled segments, could not be shown to
be significant at the alpha = 0.05 level using ANOVA with one exception (Table 5 , 3-017U on 23-Sept).
TAILED FROG WHA METHODS 2005 DRAFT
27
OKANAGAN WILDLIFE CONSULTING
Table 6. Precision (Coefficient of Variation and Standard Error as % of estimated mean) of tailed frog tadpole abundance estimates within long (200
or 300-m) reaches using 5-m sample segments compared to the use of 100-m sample sub-reaches each sampled with 5-m segments.
WHA
Date
8-011
19-Sep
26-Sep
2-Oct
Reach
Length
(m)
Samples
Sampling
Intensity
300
300
300
300
300
A
A
AB
ABC
A
Sub-reach Means1
5-m Segment samples
100-m Reaches as
samples
Pop.
Estimate1
n
CV
SE
n
CV
SE
0
1.7
2.5
3.4
0
34
154.5
103.9
98.7
115.9
169
48.9
34
47
57
18
9
9
19
28
9
32.9
22.7
38.6
54
3
3
3
3
3
118.1
32.8
11.2
14.2
117.9
68.2
18.9
6.5
8.2
68.1
1
2
3
15%
15%
31.7%
46.7%
15%
1.3
2.0
2.3
2.8
2.3
4.3
1.0
2.0
2.6
0.7
8-012
20-Sep
300
300
A
AB
15%
30%
4.0
2.0
5.7
5.0
1.3
1.5
66
69
9
18
85.8
92.2
27.1
21.2
3
3
60.5
66.8
34.9
38.6
3-014
6-Oct
200
200
A
AB
15%
30%
-
5.3
6.2
7.3
6.5
127
127
6
12
46.5
40.0
19.0
11.6
2
2
22.4
3.3
15.9
2.4
3-016S
28-Sep
200
200
A
AB
17.5%
32.5%
11.6
12.2
9.3
11.3
-
231
245
7
13
32.7
32.7
12.3
12.3
2
2
15.4
5.6
10.9
4.0
3-017U
23-Sep
3-Oct
300
300
A
A
15%
15%
8.7
4.7
11.7
5.0
7.3
6.0
174
112
9
9
31.2
43.9
9.9
13.9
3
3
24.3
13.0
14.1
7.5
8-080
22-Sep
29-Sep
5-Oct
300
300
300
A
A
A
15%
15%
15%
12.3
13.0
6.3
18.3
20.0
13.3
12.0
9.0
6.0
296
306
196
9
9
9
35.7
50.6
57.1
11.3
16.0
18.0
3
3
3
25.0
39.8
48.4
14.4
23.0
27.9
Population Estimate <100/100m
Mean for 15% intensity
Mean for 30% intensity
4
2
128.4
95.5
40.6
21.9
82.3
39.0
47.5
22.5
Population Estimate >100/100m
Mean for 15% intensity
Mean for 30% intensity
7
2
40.1
36.4
13.7
11.9
23.3
4.5
14.3
3.2
1
Sub-reach means are numbers counted per 5-m segments. Equivalent population estimate per 100-m would be the mean multiplied by 20.
TAILED FROG WHA METHODS 2005 DRAFT
28
OKANAGAN WILDLIFE CONSULTING
While my impression is still that there was some sampling effect (and that is not surprising
considering how the streambed is disturbed by this sampling), the statistics do not completely bear out this
impression. The impressions were based on some known clusters of tailed frog tadpoles in particular pools
where there were none or few found on return visits. These clusters must have dispersed after being
disturbed on the first visit. In the case of 3-017L they must have dispersed outside of the sampled 100-m
reach, or into deep pools or under large objects where they could not be sampled, since the entire reach was
sampled on the second visit. At any rate, return sampling will not always be sampling the same tadpoles in
the same distribution as the first sample, and one will be better off sampling a new randomly selected
sample (both for statistical and for biological reasons), rather than returning to exactly the same segments
on return visits.
It is possible that the reduction in observed numbers in the first week of October coincided with the
entry of tadpoles into hibernation, and was therefore not a result of any sampling methodology. When tailed
frog tadpoles enter hibernation, they stop circulating stream water over their gills, and just recirculate water
within their buccal cavities over their gills (Gradwell 1973). The water within their buccal cavities is
occasionally renewed with ambient water. They do this while clinging to the underside of rocks where they
remain for the winter. Sometimes these rocks will be drifted in with fine sands or gravels from which the
tadpoles will extricate themselves in the spring. In one site in the first week of October, two tadpoles were
found under a flat-bottomed rock, the bottom of which was flat to a gravel layer filled with sand. It did not
appear that these tadpoles could have swum under this rock, and probably had begun hibernation and let
the sand drift in around them from a minor flood event after heavy rains the previous week. Tadpole
sampling in these WHAs should probably be concluded by mid- to late-September to be sure to sample
before tadpoles have started hibernation.
While Gradwell (1973) suggests that hibernation occurs below water temperatures of 8 C, stream
water temperatures in the Cascades during this study were never above 6 C. Sampling in other years (Gyug
2000, Gyug 2001) found some tailed frog streams with water temperatures of 9-11 C in the same area up to
the end of September, but 2005 appeared to be cooler and wetter than those years. Long-term water
temperature data collected during the Merritt sensitive stream study is available for one of the WHA streams
(3-016, Henderson 2001). On WHA 3-016, mean water temperatures in July and August, 2000, were 8 C,
and the September mean was 5-6 C. Maximum summer temperatures were 12-14 C, and the September
maximum was 8-9 C. Since mean water temperatures never get above 8 C in this stream, and there was a
dense population of tadpoles that included hatchlings, then tailed frog tadpoles may have slightly different
water temperature requirements in different parts of their range if they enter hibernation at water
temperatures of 8 C in some areas.
Within-year Repeatability
For TRENDS analysis (see Power Analysis section, Gerrodette 1993a, 1993b), CV is one input factor.
However, CV as we have calculated within-sites is not the CV that is expected within that program. TRENDS
uses two methods to calculate CV. The first is as the Standard Error divided by the Mean—not the sample
Standard Deviation divided by the Mean—and the second is the Standard Deviation divided by the Mean
when the data is derived from repeat visits to a site. Thus for TRENDS power analyses, it does not matter
how we sampled within the 100-m reaches and how we calculated CV for this subsampling, as long as the SE
and accuracy are equivalent, which we found they were for both 1-m and 5-m segments when the total
TAILED FROG WHA METHODS 2005 DRAFT
29
OKANAGAN WILDLIFE CONSULTING
number of meters sampled was the same.
I calculated variability based on repeat visits within the year for given sites both with and without the
first-week of October results. I also calculated the same data for individual sites that were sampled
independently by different samples at 15% intensity, i.e., reaches sampled on the same date by A, B, and
sometimes C samples, and for reaches sampled at 30% intensity by 1-m, 3-m and 5-m sample segments
that were independently selected, but not independently sampled. The CV was calculated as the variation
around the mean of each of these independent estimates within each site.
Examining the WHAs which received more than one visit (see estimated populations in paragraph 1
of previous section) showed that SE between visits averaged 26% (n=4) with a range of 13-51% when
including the data from the first week of October. There were only 2 sites visited twice in September with SE
between visits of 0% and 1.7% when sampling exactly the same sites as the previous week. I do not
believe that this extremely low (mean 0.8% SE) would apply to tadpole sampling in general, and that SE in
the range of 10-25% would probably be more typical. Tadpoles were not caught in exactly the same
numbers on exactly the same segments. In 8-011 a total of 34 tadpoles was caught on each of the
September visits to the A samples one week apart, and in 8-080 totals of 148 and 153 tadpoles were caught
on the same A samples one week apart. Except for 2 segments in which no tadpoles were caught in either
week in 8-011, none of the individual segments had the exact same numbers caught from week-to-week on
the same segment.
Using the A, B, and sometimes C samples that were sampled concurrently as independent estimates
for population size for 200-m or 300-m reaches, the mean SE was 8.6% with a range of 0-24% (n=4).
Using the concurrent independently selected 1-m, 3-m and 5-m segments as independent estimates of
population size for 100-m reaches, the mean SE was 10.5% with a range of 5-21% (n=6).
The mean SE of all trials was 14.4% (n=14) including sites visited several times and the concurrent
sampling referred to above. SE for 13 of 14 trials was below 24%, and was always below 52%. For use in
power analysis in the software TRENDS, estimates of CV of 5% to 25% will be appropriate levels to consider.
These will represent the typical situation when one has sampled, and is intending to sample, single reaches
repeatedly (but each time by random selection of different sample segments) within a year as part of the
sampling program.
Within-site Variation Between Years
Since this project took place only in one season, it was not possible to estimate the between-year
variation at monitored reaches. Quantifying between-year variation is particularly important in the design of
a long-term monitoring program for tailed frog tadpole populations within WHAs. Data collected by John
Richardson of UBC was used to develop initial questions (Maxcy 2003), and will be used again to estimate
between-year variation using the same data as summarized in Richardson (2001). Within-year variation was
the CV for 10 x 5-m segments placed regularly along a 100-m reach, i.e., a 50% intensity sample. The mean
of this within-year variation as calculated by Maxcy (2003) (n=4 or 5 years) is presented in Figure 5.
Between-year variation looks only at the mean for each year, ignores the within-sample variation, and
calculates the variation between years for individual sites, which were sampled each year at exactly the same
segments. This data is used here even though sampling needs to be randomly selected at each visit to be
sure that statistical assumptions are valid.
TAILED FROG WHA METHODS 2005 DRAFT
30
OKANAGAN WILDLIFE CONSULTING
The between-year variation was very similar to the within-year variation (Figure 5). For sparse
populations estimated <100 tadpoles per 100-m (n=8), within-year and between-year CVs ranged from
about 20 to 110%. The mean within-year CV was 54% and the mean between-year CV was 62%. For
dense populations >100 tadpoles per 100-m (n=2), CV ranged from 9 to 50%, mean within-year CV was
28%, and the mean between-year CV was 32%. The variation is also in the same range as the within-year
CV calculated in this pilot project on the east slope of the Cascades where CV of 30-50% were expected for
tadpole populations >100 per 100 m, with higher CV for less dense populations. Within-year SE (for
application to the TRENDS software) was not available for the within-year data as I did not have the raw
data on hand. However, since SE = CV/sqrt(n), and n=10 for each site within each year, then the average
within-year SE would be about 17% for sparse populations, and 9% for dense populations. This would be
the “CV” to put into the TRENDS power analysis software.
Figure 4. Between-year and mean within-year Coefficients of Variation (S.D./mean) for 10 tailed frog
populations in the Chilliwack River valley sampled by 10 5-m regularly-spaced segments within
120
100
CV %
80
60
40
20
0
0
50
100
150
200
Est number tadpoles/100m
Between-year
Mean within-year
100-m reaches. Mean within-year data as summarized in Maxcy (2003) based on unpublished
data provided by John Richardson, and between year data from Richardson (2001).
TAILED FROG WHA METHODS 2005 DRAFT
31
OKANAGAN WILDLIFE CONSULTING
Tailed Frog Age Class Distribution
Size Class Distribution of Tadpoles
Tadpole size class distributions based on total length (TL) measured to the mm can be used to
estimate age class distributions based on the detailed work of Brown (1990) which corrected the previous
assumptions about tadpole age class determinations based on Metter (1964). Up to five tadpole cohorts
were found in a single 300-m reach (Figure 5). These included Cohort 0 (hatched 2005) that were found in
only two sites and only in very small numbers. They were always <23 mm, and were only found in late
September and early October. Cohort 0 tadpoles are generally not available for sampling in the year of
hatching in the east Cascades of B.C. They are too small and immobile to be among the general tadpole
population, and tend to stay under the large rocks or boulders in deep pools where the eggs were laid, and
which are generally very difficult to locate.
By mid to late-September Cohort 1 (hatched 2004) tadpoles were generally 29-35 mm TL and the
most abundant cohort. Cohort 2 (hatched 2003) were 35–40 mm TL and slightly less abundant than Cohort
1. Metter (1964) lumped Cohorts 1 and 2 together because there are no clear size distribution gaps between
them by late summer. Cohort 3 (hatched 2002) were 41-48 mm and much less abundant than Cohorts 1
and 2, and a few Cohort 4 (hatched 2001) were found that had yet to metamorphose into adults.
There was some overlap in TL of cohorts 1-4 so that cohorts cannot be distinguished simply by
looking for peaks and valleys in the graphed size distribution (Brown 1990). Cohorts 1 and 2 overlapped in
TL from about 34-37 mm (and possibly with a wider overlap) but could usually be distinguished in the hand
because Cohort 2 tadpoles looked distinctly broader and appeared heavier overall than Cohort 1 tadpoles of
the same length. However, we did not make this distinction in the field for each tadpole because by the time
we were aware that we needed to do this to distinguish cohorts, the sampling had been completed. Cohort
3 tadpoles almost always had small hind legs in the 2-6 mm length range. Generally Cohort 4 tadpoles were
missing from the streams because most would have metamorphosed into small frogs that were 20-25 mm
SVL by autumn. The few tadpoles found that were presumed to be Cohort 4 were generally >50 mm TL,
had very large hind legs (up to 10 mm), and given the lateness in the season, would probably spend another
winter in the streams as tadpoles before metamorphosing the next summer.
The size/age class distribution in each of the seven streams appeared to be slightly different from
the others in that not all cohorts were present at all sites, and cohort size ranges differed slightly in some
sites (Figure 5). In particular, WHAs 3-004U, 3-014 and 8-011 appeared to be lacking Cohort 1. This could
have been because reproduction failed in 2004, the year that Cohort 1 would have hatched. Or it could have
been because the sites were not natal reaches where reproduction was occurring and all tadpoles had
migrated upstream or downstream to the site, or had been washed down to the site during annual flood
conditions which could vary quite widely between years and affect cohorts differently. In WHA 8-011,
breeding adult male and female frogs were found, so that reproduction is probably occurring in the reach.
Any missing cohort would probably have resulted from reproductive failure due to factors that would affect
survivorship of just the youngest cohort. Failure of one or more cohorts could be attributable to flood
conditions, influx of sediment loads, streams drying, or other factors that would affect the immobile egg
stage, and the relatively immobile hatchling stage compared to older mobile tadpoles (DeVlaming and Bury
1970).
TAILED FROG WHA METHODS 2005 DRAFT
32
OKANAGAN WILDLIFE CONSULTING
Cohort 3 appeared to be larger in 3-004U and in 3-014 than in other WHAs, or else Cohort 3 was
missing, and Cohort 4 was smaller than in other streams, and still in the stream in large numbers. It is
probable that growth rates vary considerably depending on stream conditions, particularly temperature and
algal biomass. The tadpoles from 40-50 mm may be almost all from Cohort 3, even if the total size
distribution considering all WHAs appeared to have two distinct peaks within the 40-50 mm range. Similarly,
the “missing” Cohort 1 in some streams may be represented by larger individuals that look like Cohort 2 in
some streams. Some of these streams may be on 3-year, rather than 4-year tadpole cycles if growth and
developmental rates vary considerably.
In the geographic range of tailed frogs, southerly and lower elevation tadpoles may have 1-year or
2-year larval periods, compared to 3-year and 4-year in more northerly and higher elevation populations
(Bury and Adams 1999). The amount of local variability is unknown. Returning to the sites next year for
further monitoring to follow the progress of cohort growth would determine if some cohorts were actually
missing, or if growth rates vary enough to mask or confound determination of age class distributions.
To get some idea of the relative abundance/survivorship of tailed frog tadpoles, I summed the
numbers of tadpoles by size classes for streams which contained Cohorts 1 (26-35 mm), 2 (35-40 mm) and 3
(41-49 mm). While this is slightly arbitrary, and the dividing point for cohort size is not likely identical in each
stream, this will give some idea of relative abundance that might be expected in any given stream. There
were 447 Cohort 1, 231 Cohort 2 and 165 Cohort 3 tadpoles. This would translate to survivorship of 0.5
from Cohort 1 to Cohort 2, and 0.7 from Cohort 2 to Cohort 3. An age class table beginning at Cohort 1
would be Cohort 1; 1.00; Cohort 2, 0.50; Cohort 3 0.35. A complete larval age class-survivorship table could
be drawn up if we knew how many eggs or hatchlings there were in a stream, but only the oldest three
cohorts can be sampled in streams with egg-laying sites being very difficult to find.
Abundance of Adults
Very few adults were found, and in-stream daytime searches are not the most efficient method to
find adult tailed frogs. For WHAs where >1 tadpoles were found, adults made up between 0 and 19% of
the total tailed frog sample (Table 1) There was too much variability in the percentages of adults found to
estimate adult population size reliably, or to use this as any indicator for WHA monitoring. In particular, it is
not known if the numbers found in-stream reflect actual numbers. The least that we can say is, if breeding
adult males (>37 mm SVL) and breeding adult females (>44 mm SVL), and juvenile adults, and a full range
of tadpole cohorts are found in a stream reach, then reproduction is probably occurring there, and the site
can be termed a natal reach. The populations of these natal reaches are probably the most stable
compared to other reaches over the 12-year typical life span of a tailed frog, and these will probably make
good sites for WHA monitoring. Natal reaches will be a subset of the core reach since reproduction and
stable populations may not occur at all parts of the core reach. If breeding and non-breeding adults are not
found at a reach, and there are one or more tadpole cohorts lacking, then the site might not be a natal
reach, and may not be the best site for WHA monitoring. If tadpole populations only reflect immigration to a
site, then we would expect numbers to be quite variable since the factors leading to immigration are not
necessarily known, and are probably quite variable. Unfortunately, whether a site is a natal reach or not
cannot be determined simply by looking at a site. It can only be determined by sampling tailed frog
populations intensively enough to determine the presence of all possible cohorts of tadpoles, and all age and
sex classes of adults.
TAILED FROG WHA METHODS 2005 DRAFT
33
OKANAGAN WILDLIFE CONSULTING
35
30
Tadpole Count
25
20
15
10
5
0
20
24
26
28
30
32
40
42
44
3-
38
52
4
00
50
4
01 U
48
3-
46
3-
Tadpole TL (mm)
36
3-
34
0
08 2
801
8- 11 +U
0
L
7
801
6
01
22
Figure 5. Coastal Tailed Frog tadpole size class distribution for 7 WHAs on the east slope of the Cascade Ranges, Sept. 19-Oct. 7, 2005.
TAILED FROG WHA METHODS 2005 DRAFT
34
OKANAGAN WILDLIFE CONSULTING
WHA
LONG-TERM MONITORING RECOMMENDATIONS
Best Indicators for Tailed Frog WHA Population Monitoring
There is a high mortality rate of tadpoles (that might be as high as 90% if we would try to construct
a full survivorship table) and amphibian larval population sizes and survival rates are generally highly
variable. Each female tailed frog produces 30-80 eggs every second year, and is reproductive for 4-6 years
of a possible 13-year life span. Monitoring of adult populations would probably be a much better and more
stable indicator of actual populations. For all the effort that has gone into tailed frog research over the years,
there are no density estimates of adults. The only study that might have been able to provide a density
estimate per linear stream m was Daugherty and Sheldon (1982). They captured and marked 543 adults in
an 80-m stream section in a 5-year period in Montana but never did estimate numbers resident on their 80m reach in any given year. Nor did they provide estimates of ratios of juvenile adults that may have been
transients on the site to adults they might have considered resident. Their study required mark-recapture of
adults, and about 20-30 nights per summer. Monitoring of adult populations is too time consuming and
intensive to be considered as anything but applied research.
Declines in tadpole populations have been noted where there have been catastrophic events, e.g.,
flash floods with debris flows (Metter 1968), Mt. St. Helens volcanic eruption (Hawkins et al. 1988), and
wildfires (Pilliod et al. 2004). Metter (1968) and Hawkins et al. (1988) noted complete absence of tailed frog
tadpoles after those disturbances. Pilliod et al. (2004) noted failure of one year of reproduction, after which
the population recovered, but results were variable among areas. (I have only seen an abstract of this
conference paper and as far as I know this research has not been published yet so is hard to fully evaluate.)
Tailed frog hatchlings and eggs are more sensitive to water temperatures and probably to other
environmental factors than older tadpoles. No other studies have examined populations for long enough to
detect declines over long periods in response to environmental conditions. Studies on tailed frog tadpole
populations and distributions have almost always been retrospective, i.e., comparing densities in different
types of streams, and/or in different types of landscapes, and/or with different surrounding conditions such
as forest stand age. Long-term monitoring of tailed frog populations beyond a 5-year timeframe is not
something that has been attempted before, or at least not documented if it has been attempted before.
Any monitoring of tailed frog tadpole populations must include reliable estimates of population size
and age-class distribution. Only by looking at the tadpole cohorts present in a stream can one tell if
population size may have changed because a single cohort is missing, or because numbers are missing from
each and every cohort. When looking for cause-and-effect relationships, one would look for evidence of
large events (e.g. flash floods) that would have wiped out any vulnerable age classes if one or more cohorts
were missing from the stream. If numbers were missing from every cohort, then habitat suitability may have
declined gradually rather than catastrophically. One would look for a different class of possible causes, such
as declines in adult numbers because of unsuitable surrounding habitat, infill of stream crevices by fine
sediments, moderate but not severe bed load movement or scouring, changes in stream temperature
regime, or gradual canopy closure resulting in reduced algae production for tadpole forage. Examination for
“missing” cohorts would require that baseline data be from 2 consecutive years to determine the size
distribution of cohorts present, and then follow-up sampling at 3-year, or more frequent, intervals when and
if impacts are suspected.
TAILED FROG WHA METHODS 2005 DRAFT
35
OKANAGAN WILDLIFE CONSULTING
Power Analysis
(I have copied portions of this section directly from Appendix 3 of Maxcy (2003) so some sentences might be
recognizable from that document.)
Version 1 (FREP 2005) did not address levels of detection of changes or trends in tailed frog tadpole
abundance except in the most general sense, i.e., declines in abundance were included as an indicator in a
suite of indicators without considering the power to detect those observed declines, or whether those
declines might be part of natural variations in population size. There was also ambiguity as to how declines
would be treated as part of the indicators, i.e., sometimes they appear to be on a WHA-by-WHA basis, and
at other times they are part of the entire collection of WHAs. Power to detect changes within single reaches
within WHAs, within a WHA as a whole, or within a suite of WHAs within a region are three very different
ways to frame the question, and each requires its own approach, its own study and sampling design, and its
own power analysis.
Power analysis evaluates the ability to detect true trends in the variable(s) of interest. Before
any monitoring program is started, it is important to evaluate whether the sample design has the power
to detect trends in the population, should they exist. This power analysis will be limited to the detection
of rates of change in abundance within a single monitored reach within a WHA. This monitored reach
may be 100-300 m in length since this project has shown that over this short length and within relatively
uniform alluvial core reaches, tailed frog distribution is also relatively uniform and reach length does not
affect the results.
Regression analyses will only have much power to detect trends when there have been at least 4
sampling sessions unless the effect size is very large. Four sampling sessions would take 4 years if done
annually, but would take much longer if sampling is to be done at less than annual intervals. When there
are <4 sampling sessions from different years, ANOVA tests will be the method to detect differences in
means between years. ANOVA tests will also apply when changes in population size are not gradual but
are stepped, which regression analyses are relatively poor at detecting. ANOVA tests are most powerful
and least susceptible to any violations of assumptions when sample size is even among samples, so it is
important to use a consistent sampling methodology, whatever that methodology may be. When looking
at longer term trends, sampling methodology in a given year is not as important as long as the methods
result in predictable variation within year, and accurate results from year to year, since only the mean
estimate of any given year is used in the final analysis, not the within-year variation.
TAILED FROG WHA METHODS 2005 DRAFT
36
OKANAGAN WILDLIFE CONSULTING
Trend Analysis
Power analysis for long-term trends based on regression analyses was conducted using the freeware
program TRENDS 3.0 (Gerrodette 1993a, 1993b, but version 3.0 is from 2000). The null hypothesis in
this case is that there is no trend in the data, and the population neither increases nor decreases over
time. The input of TRENDS includes five parameters:
1. n = the number of time steps. In this case, it is the number of years over which we would like to
detect a trend, or the number of years a reach would be monitored. The software allows for
sampling at multi-year or irregular intervals. Extensive monitoring is unlikely to be undertaken
annually, but might be considered on a 3-year or 5-year basis unless extensive forest harvesting was
occurring in a watershed. Regression analyses are most powerful with more sampling at each end of
the independent variable (i.e., the x-axis or time) so it is not necessary to sample at even intervals.
Frequent initial annual baseline sampling (n=2 or 3), longer intervals in the intervening period (e.g.
every 5-years), and annual sampling when routine evaluations indicate there is a possibility of
impacts (n=2 or 3) is an alternative to sampling at even intervals. In addition, sampling effort per
year need not be uniform. Should impacts be suspected, increased sampling resulting from moving
to an intensive monitoring scheme can be incorporated into the regression analyses. TRENDS can be
used to calculate the power of designs using both uneven and/or irregular sampling.
2. r = rate of change that occurs between sampling occasions (e.g., between years), or overall change
(e.g., over the entire length of the sampling program). We, as biologists, need to estimate the size
of the effect or rate of change, which we consider significant biologically. This should be outside of
the natural range of variance in the population, and be a change that would be significant to
population processes—which may not necessarily be well known or understood. I would suggest that
we would want to detect at least a 50% change in tadpole populations over any time period if this
change was occurring evenly across cohorts. 50% was chosen because it is much higher than typical
SEs of 20-30%, and will therefore be well outside of the range of natural variability of within-year
sampling. Changes of <50% in tadpole populations may be difficult to detect in some instances
(particularly when numbers are low) because of high SE, but setting the change at >50% may result
in real declines not being detected. This number is not fixed but could be varies. Changes that occur
because cohorts are missing will not require any rate-of-change or power analysis but would be
considered significant on their own and would trigger intensive monitoring.
3. CV = coefficient of variation (SE/mean of single sample using within-sample variance, or S.D./mean if
sample is multiple samples of one site) of the first estimate of abundance in the time series, which
for tailed frogs is very similar to between-year CV. There are options in the software to change effort
per annual sample with adjustments automatically made to CV within the program. Based on this
pilot project, CVs from 5% to 40% will be appropriate to examine.
4. CV is proportional to 1/SQRT(Abundance) in the case of tailed frog tadpoles.
5. α = the probability of a Type I error, i.e., rejecting the null hypothesis (there is no trend) when it is
actually true (there is a trend). Here α/2 is the probability of detecting a decline since trends can be
positive or negative. For this project, α/2 is the probability of incorrectly finding a trend, and
therefore triggering intensive monitoring unnecessarily.
TAILED FROG WHA METHODS 2005 DRAFT
37
OKANAGAN WILDLIFE CONSULTING
6. Power = (1-β), the probability of correctly determining a trend when there actually is a trend. β =
the probability of a Type II error, i.e., accepting the null hypothesis (there is no trend) when it is
actually false (there is a trend).
The balance of α and β for a given n and CV can be considered in the power analysis depending
on the consequences of the different types of error. We need not restrict α or β to any given level. We
do not want to make an error and accept the null hypothesis if there is no trend because that would
trigger unnecessary concern and costs as it would trigger a more detailed level of investigation: so we
should keep α low. However, do we not want to make an error and accept the null hypothesis of no
trend when there actually is a trend that is biologically significant: so we should keep β low (or
conversely keep power high). The best option is probably to find the point where α = β for a given CV
and rate of sampling so that the probability of the two types of errors are balanced.
For CV <10%, and balanced α and β of 0.20, extensive monitoring at levels used in this pilot
project would detect 50% total tadpole population declines within 4 sampling sessions (Table 7). For
annual sampling, this would be 4 years but for sampling at 5-year intervals, this would be 20 years. For
CV = 20%, and balanced α and β of 0.20, extensive monitoring at levels used in this pilot project would
detect 50% total tadpole population declines within 6 sampling sessions (Table 7). For annual sampling,
this would be 6 years but for sampling at 5-year intervals, this would be 30 years. CV >20% have very
little power to detect total population changes of 50% given that it would take 11 sample sessions to
detect such a change. This would be 16 years at α and β of 0.20 if sampling was done annually, but
much longer if sampling was less frequent than annually.
An unbalanced sampling design where initial baseline studies are done for 2 years, then at less
frequent intervals, then at frequent intervals when impacts might be suspected, will be the most efficient
sampling scheme. The example in Table 8 (final line) is given for an 11-year period, i.e. the initial
sample and then 10 years after. There are two initial (baseline) samples, then a sample is made in the
6th year, then 2 final samples at the end of the 11-year period. For a given power, this design can detect
much smaller population trends (or conversely can detect a 50% decline with much higher power) than
either sampling every fifth year, or sampling every 3rd year for an equivalent number of samples, and is
equivalent in power to sampling every second year, and not far off the power of annual sampling.
TAILED FROG WHA METHODS 2005 DRAFT
38
OKANAGAN WILDLIFE CONSULTING
Table 7. The number of samples (annual or less frequent) required before a 50% total tadpole population
change could be detected predicted by TRENDS regression power analysis as software.
n samples at which total 50% population change
can be first detected.
α=β
Power (1-β)
0.1
CV%1
5
10
15
20
25
40
0.9
4
6
7
13
20
>50
0.2
0.8
3
4
5
6
16
42
0.25
0.75
3
3
3
5
11
30
1 CV
= Std. Error as % of mean.
Table 8. The minimum detectable total percentage tadpole population reduction over an 11-year period
where α = β = 0.20 using different yearly sampling regimes as predicted by TRENDS regression
power analysis software.
Minimum detectable % total population change
over an 11 year time period
Sampling Interval
n samples
( where first sample = Year 1)
CV%1
5
10
15
20
25
40
Every year
11
11
22
35
47
61
-
Every 2nd year
6
15
31
48
66
85
-
Every 3rd year (13 year
period)
5
19
41
64
90
-
-
Every 5th year
3
32
68
-
-
-
-
2 baseline annual samples,
(3 year-gap),
1 sample,
(3- year gap),
2 annual samples
5
14
30
46
63
82
-
1 CV
= Std. Error as % of mean for initial within-year sample.
TAILED FROG WHA METHODS 2005 DRAFT
39
OKANAGAN WILDLIFE CONSULTING
Sample-to-Sample Comparisons
Power analysis for one-way ANOVA from Statistica 6 was used to estimate power for short-term
trends for which regression analysis of trends will not be useful. In particular this will apply to comparisons
of tadpole populations from a single year to a baseline year before there are enough samples for trend
analysis, or where the trends are not linear or exponential, i.e., they are stepped and quick rather than being
expressed in long term gradual declines. We would like to have relatively high power (1-β >80%) without
raising α unnecessarily high (α<20%) to detect true declines of 50% in a tadpole population from one
time period to the next. To rephrase that for power analysis, if we detect a decline in abundance of
50%, can we determine that this decline is statistically significantly different from the original abundance.
I will only examine here the case where there are two time periods compared but the analysis could be
extended to more than two cases.
ANOVA is dependent on sample size, and not just variation, but within this tadpole sampling, any
change in variation caused by sample segment length is adjusted for by increasing sample size when
constant sampling effort (e.g. 30%) is applied. Therefore the power analysis below is just for one case,
(n = 10, 5-m segments over 300-m, 15% sampling effort), but the results will be very similar for other
combinations of sampling effort, total length over which samples were taken, and individual sample
segment length as long as the SE as % of mean is similar in each case.
To detect a 50% change in abundance from one time period to another, for n=10, for CV <30%,
both α and β were <0.05; for CV = 35%, α = β = 0.1, for CV = 50%, α = β = 0.19, and for CV = 60%, α
= β ≈ 0.25. Therefore power will be very good when CV <30%, and not be acceptable if CV increases
above 60%. Where CV is found to be above 50%, we should make efforts to make it lower by increasing
sample size.
Mean CV was 42% for 10 5-m segments over 300-m for dense populations, and 128% for sparse
populations (Table 4). 42% CV has a power of 87% and α = 13% to detect a significant difference of
50% in population numbers at n =10, so that sampling in dense populations can achieve acceptable
power. Sampling at 30% intensity over 100-m achieved CV of 50% for 5-m segments, 100% for 3-m
segments and 120% for 1-m segments on average (Figure 2). Power of each of these combinations to
detect a 50% change was around 0.25, 0.40 and 0.28 respectively. Except for the 3-m segments that
had poorer precision in this trial than in the nested sampling, there was not much difference in power to
guide the choice of sample segment length. However, power is very sensitive to sample size, so that
sampling 10 5-m segments over 300-m had higher power to make a correct decision (87% vs 75%) and
a lower chance of incorrectly triggering extensive monitoring (7% vs 12%, i.e., α/2) than sampling 6 5-m
segments over 100-m because of the increase in sample size from 6 to 10.
For sparse populations, there will be very poor power to detect a 50% change in numbers from
one sampling session to the next unless sample size is increased. For typical CVs (see Tables 4 and 6) of
80%, 125% and 200%, sample size of each group must be 23, 58 and 150 respectively to achieve
acceptable power of 80% with α = 20%. For a 100-m reach, none of these sample sizes are achievable.
It is not possible to put 23 5-m segments, 58 3-m segments or 150 1-m segments into 100 m. Reach
length must be longer than 100 m, and should be 200 or 300 m. Conducting 100 to 150 m of areaconstrained searches will only be possible within one day on structurally simple small streams with very
few tadpoles, and is not realistically possible on wider streams with predominant beds of large cobbles
TAILED FROG WHA METHODS 2005 DRAFT
40
OKANAGAN WILDLIFE CONSULTING
and boulders.
There will be definite limits to how effectively we will be able to statistically determine changes in
sparse tadpole populations through low-level intensity monitoring that will make them poor choices for
long-term monitoring. Monitoring of these sparse populations will more likely rely more heavily on ageclass distribution of tadpoles. Absent or severely reduced cohorts are more likely to trigger more
intensive monitoring rather than declines in abundance that will be very difficult to properly detect.
Best Options for Tailed Frog WHA Tadpole Monitoring
Framing the Question
The goal of WHA effectiveness monitoring is not to know everything there is possible to know about
a very small portion of the WHA. The real question is: what is the state of the population in the entire WHA.
Only if that small portion is representative of an entire WHA will this method be valid, and this can only be
determined by sampling within the entire WHA, or at least the entire core reach for tailed frogs. FREP
(2005) suggested sampling at one short (100 m) downstream reach because this should reflect upstream
processes throughout the basin. However, this should be demonstrated for tailed frogs before it is accepted
as the best monitoring indicator for a population within a WHA. If tailed frog populations vary within WHAs,
and are not in synchrony, i.e., there are source areas and sink areas within core reaches inside WHAs, then
one spot at the downstream end of a WHA may reflect relatively little of the population processes within the
WHA. Undertaking a simple monitoring project to determine how representative single downstream reaches
are of entire WHAs would be a fairly simple study requiring multiple sampling reaches within a WHA, but
would take some time and effort.
If a population is seen to decline below a threshold that would trigger more intensive sampling, then
the question will become, have tadpoles declined within the entire WHA, or is this result unique to this one
site? At that point, further randomly selected (or purposely selected within a retrospective study design to
detect impacts) reaches will need to be assessed. But there will be no prior knowledge of what populations
were in those reaches, so no definitive conclusions will be able to be drawn unless the impacts and causes
are very dramatic and obvious.
Framing of the question is very important to power analyses. Whether the question is about a WHA
tailed frog population, or about the population of a small reach within the WHA, does make a difference to
power calculations. Power calculations assume independent randomly selected samples. Returning to the
same site within a WHA to monitor populations violates this assumption if the question is about the
population of the WHA as a whole. Power will be decreased, not increased, by returning to the same sites
over and over if the question is about the state of the population in the whole WHA. If the question is about
the state of the population in one reach, then sample sites within that reach must be randomly selected on
each visit, or power calculations will not be valid. One does not gain anything statistically or biologically by
returning to the same exact 5-m sample sites, and returning to the exact same 1-m sample sites would be
almost impossible.
Other questions that we would like to know are: Are these closed populations we are sampling?
What distances do tadpoles move upstream or downstream over the course of a year, or over the course of
the 3-4 years they spend in the streams? Sampling over what length of stream would we be sampling a
closed population? Otherwise, if tadpoles move upstream or downstream based on certain factors or
TAILED FROG WHA METHODS 2005 DRAFT
41
OKANAGAN WILDLIFE CONSULTING
conditions, sampling just one short reach will not let us know what those conditions may be. If a reduction is
found in one short reach in a WHA that triggers more intensive sampling, and the reduction is not found in
other short reaches within the WHA, do we conclude that some factor acted only on the reach we were
monitoring, or were populations reduced by a similar factor in all reaches but baseline densities were higher
in the other reaches.
Recommendations
We wish to use the least intensive sampling method with the best balance of precision, accuracy and
highest power, both to reduce time and cost of sampling individual WHAs, and to reduce potential
disturbance to the streambed and the tailed frog population. I would recommend triggering of more
intensive monitoring if tadpole numbers are seen to decline by 50% or greater, and this decline is statistically
significant as determined at the balance point where α = β and both are <0.25. I would also recommend
that intensive monitoring be triggered if one or more tadpole cohorts are found to be absent from a
monitored reach where they were previously present.
The first recommendations will be the best way to sample single monitored reaches. In a dense
uniform population, monitoring a reach of 100-m at 30% intensity will usually produce acceptably low SE of
20% using any sample segment lengths of 1-m or 5-m (and perhaps 3-m if further trials should indicate 3-m
segments can have SE as low as 1-m or 5-m segments). In low density populations, sampling effort should
increase to achieve an SE within 40% of the mean if possible. This would mean sampling reaches longer
than 100-m at 30% intensity or greater. It will be important to keep track of results in the field while
sampling (bring your calculator) so that sample size can be increased in the same sampling session by
increasing reach length (since going back over monitored reaches to resample is not valid because tadpole
distribution has been disturbed). Sample segments of any length may be used but 1-m segments tend to
have upward bias at low intensities and in low densities, 3-m segments did not perform well in precision in
our trials, and 5-m segments performed poorly if there were uninhabited sections of 10-15 m length within
the monitored reach. 5-m segments tended to be more efficient (more accurate, higher precision) at 15%
intensities than other segment lengths, but this advantage did not hold at 30% intensities.
It is not necessary to dictate that sampling be of a certain segment length for tailed frogs provincewide. It is only necessary that once a certain sampling scheme is applied to a certain WHA that this scheme
be repeatable in the future. On a province- or region-wide basis comparisons of WHA populations will be
made with the estimated population size of each of the WHAs in the set, which will not require knowledge of
the within-sample (i.e., within WHA) variation, only the confidence that the populations of the individual
WHAs were estimated within a certain precision, and with predictable accuracy. If the question becomes,
does the population of the monitored reach of WHA X differ from the monitored reach of WHA Y, then
sampling methodology must be consistent. However, this is not one of the questions that is likely to be
required of WHA monitoring on a wide-scale basis.
In addition, presence of size-class/age cohorts of tadpoles are just as important as the tadpole
population numbers as an indicator for extensive monitoring. Sampling must be of an intensity that we have
confidence in the age class determination for tadpoles, which will generally require a sample of 50 or more
tadpoles per monitored reach.
TAILED FROG WHA METHODS 2005 DRAFT
42
OKANAGAN WILDLIFE CONSULTING
Extensive monitoring sample intervals should be annually for the first 2 years to establish baselines.
Monitoring after that could be as infrequent as every 5 years depending on the relative susceptibility of the
population to impacts based on examination of routine or stream morphology indicators. Should the relative
susceptibility of the population change due to extensive timber harvesting in the WHA basin, then more
frequent monitoring would be needed. This more frequent monitoring could be annually, or every second or
third year depending on the expected or observed levels of impacts.
The levels of intensive monitoring triggered by extensive monitoring would depend on the levels of
impact found. First steps would be to determine if the impacts to the tailed frog populations were WHA
wide, were part of a general trend in the region dictated by climate or weather or other uncontrollable
factors, or were not apparent elsewhere, and were particular to the monitored reach. Different types of
cause-and-effect investigations would be triggered depending on the nature, level and types of impacts
found.
The second recommendation is to answer concerns over how representative the selected sample
reach is of the entire WHA before any impacts might be found to occur. A downstream monitored reach may
not be representative of stream processes in a WHA if there are upstream buffers such as wetlands, lakes, or
low-gradient unconfined stream reaches that would absorb the impacts of sediment influxes, debris flows or
flash floods. How representative a single monitored reach is of an entire WHA should be determined
empirically, not simply assumed.
The population of the monitored reach as part of a whole WHA or whole stream population may be
addressed by consideration of relative abundance and/or age class distribution from previous data collected
in the WHA during time-constrained searches or other research. If no other data is available, then one
approach would be monitoring one short 100-m reach within a WHA intensively (30% sample) as part of the
extensive monitoring, and then examine other randomly selected reaches within the WHA just once at lower
intensities (e.g. 15% sample) to confirm if they are similar to, or different from, the monitored reach. The
random selection may be stratified by stream gradient, confinement or other morphological features. This
approach would work in densely populated WHAs where several reaches could be sampled lightly in one day,
depending on access and on how much other data was being collected on the same day, and where 15%
samples provide relatively reliable information about short 100-m reaches. In sparsely populated WHAs,
more intensive sampling (30-50%) of reaches >100-m in length would be required just to establish
acceptable baselines, and probably only one reach could be sampled in one day. However, information
about population size and structure in other reaches of low density WHAs would still be valuable for longterm monitoring, especially if low density populations are more susceptible to local extirpation than higher
density populations. Therefore examination of monitored reaches within entire WHAs should be examined as
part of extensive monitoring for a randomly selected subset of WHAs.
TAILED FROG WHA METHODS 2005 DRAFT
43
OKANAGAN WILDLIFE CONSULTING
LITERATURE CITED
Adams, M.J. 2000. A monitoring Design for Stream Amphibians. Pages 39-41 In Inventory and Monitoring
of Amphibians in North Cascades and Olympic National Parks 1995-1998 (R.B. Bury and M.J.
Adams, eds.). USGS Forest and Rangeland Ecosystem Science Centre, Corvalis. OR.
Brown, H.A. 1990. Morphological variation and age-class determination in overwintering tadpoles of the
tailed frog, Ascaphus truei. J. Zool., Lond. 220:171-184.
Bury, R.B. and M.J. Adams. 1999. Variation in age at metamorphosis across a latitudinal gradient for the
tailed frog, Ascaphus truei. Herpetologica. 55(2):283-291.
Bury, R.B. and P.S. Corn. 1991. Sampling methods for amphibians in streams in the Pacific Northwest.
USDA For. Serv. Gen. Tech. Rep. PNW-GTR-275, Portland, Oreg. 34 pp.
Daugherty, C.H., and A.L. Sheldon. 1982. Age-specific movement patterns of the tailed frog, Ascaphus
truei. Herpetologica 38:468-474.
DeVlaming, V.L. and R.B. Bury. 1970. Thermal selection in tadpoles of the tailed frog, Ascaphus truei.
Journal of Herpetology 4:179-189.
Dupuis, L. and P. Friele. 2002. Distribution of Ascaphus montanus in the Yahk River and neighbouring
watersheds. Report to Tembec Industries and Columbia Basin Fish and Wildlife Compensation
Program. Cranbrook and Nelson, BC. 31pp.
Forest and Range Practices Act Resource Evaluation Program (FREP). 2005. Protocol for conducting
routine and extensive effectiveness evaluations for tailed frog wildlife habitat areas: Version 1.
Draft report prepared by L. Dupuis and P. Friele for the FRPA Forest Resource Evaluation
Program. Ministry of Water, Land and Air Protection and Ministry of Forests. Victoria, BC.
Gerrodette, T. 1993a. Program TRENDS: User's Guide. Southwest Fisheries Science Center, La Jolla, CA
Gerrodette, T. 1993b. TRENDS: software for a power analysis of linear regression. Wildlife Soc. Bull.
21:515-516.
Gradwell, N. 1973. On the functional morphology of suction and gill irrigation in the tadpole of
Ascaphus, and notes on hibernation. Herpetologica 29:84-93.
Gyug, L.W. 2000. Tailed Frog Inventory, Year 2000, Merritt Forest District. Report prepared for B.C.
Ministry of Environment, Lands and Parks, Kamloops, B.C.
Gyug, L.W. 2001. Tailed Frog Inventory, Merritt Forest District: Project Report 2001. Report prepared
for B.C. Ministry of Environment, Lands and Parks, Kamloops, B.C.
Gyug, L.W. 2002. Tailed Frog Wildlife Habitat Area Proposals, Merritt Forest District. Prepared for B.C.
Ministry of Water, Land and Air Protection, Kamloops, B.C.
Hawkins, C. P., L. J. Gottschalk, and S. S. Brown. 1988. Densities and habitat of tailed frog tadpoles in
small streams near Mount St. Helens following the 1980 eruption. Journal of the North American
Benthological Society 7:246-252.
Hawkins, Charles P. and J.R. Sedell. 1990. The role of refugia in the recolonization of streams
devastated by the 1980 eruption of Mount St. Helens. Northwest Science 64(5): 271274.Resources Inventory Committee. 1999.
Henderson Environmental Consulting Ltd. 2001. Stream Temperature in the Spius Creek Watershed
Second Year Results: 2000 summer /fall. Unpublished report prepared for Aspen Planers Ltd.
TAILED FROG WHA METHODS 2005 DRAFT
44
OKANAGAN WILDLIFE CONSULTING
Merritt Division, Tolko Industries Ltd. Nicola Valley Division, Weyerhaeuser Canada Ltd. Merritt
Division, Merritt, B.C.
Maxcy, K. 2003. Indicators and methods for effectiveness monitoring of tailed frog wildlife habitat areas.
Report prepared for Biodiversity Branch, Ministry of Water, Land, and Air Protection. Victoria,
B.C.
Metter, D.E. 1964. A morphological and ecological comparison of two populations of the tailed frog,
Ascaphus truei Stejneger. Copeia. 1964:181-195.
Pilliod, D.S., S.P. Corn, B.Bury and E.J. Hyde. 2004. Effects of wildland fires on stream amphibian
populatinsint he greater northwest. Northwest Scientific Association 77th Annual Meeting,
Ellensburg, WA. Abstract obtained from
http://www.vetmed.wsu.edu/org_NWS/Files/2004%20meeting/
Quinn, T., M. Hayes, D.J. Dugger, T.L. Hicks and A. Hoffman. 2004. Comparison of two tailed frog
sampling methods in headwater streams of southwest Washington. Forest Practices Adaptive
Mangement Science Conference, Feb. 24, 2004, Olympia, WA. Abstract obtained from
http://www.dnr.wa.gov/forestpractices/adaptivemenagement/conferences/
Richardson, J. 2001. Tailed frogs and the effects of forestry practices, final project report 1996-2001.
Forest Renewal B.C. Project No. HQ96351-RE.
TAILED FROG WHA METHODS 2005 DRAFT
45
OKANAGAN WILDLIFE CONSULTING