Differential Influence of Weather on Regional Quail Abundance in Texas
Author(s): Andrew S. Bridges, Markus J. Peterson, Nova J. Silvy, Fred E. Smeins, X. Ben Wu
Reviewed work(s):
Source: The Journal of Wildlife Management, Vol. 65, No. 1 (Jan., 2001), pp. 10-18
Published by: Allen Press
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DIFFERENTIAL
INFLUENCEOF WEATHERON REGIONALQUAIL
ABUNDANCEIN TEXAS
ANDREWS. BRIDGES,1
2 Departmentof Wildlifeand FisheriesSciences, Texas A&MUniversity,College Station,TX 77843,
USA
MARKUSJ. PETERSON,3Texas Parks and WildlifeDepartment,210 Nagle Hall,Texas A&MUniversity,College Station,TX
77843, USA
NOVAJ. SILVY,Departmentof Wildlifeand FisheriesSciences, Texas A&MUniversity,College Station,TX 77843, USA
FREDE. SMEINS,Departmentof RangelandEcology and Management,Texas A&MUniversity,College Station,TX 77843,
USA
X. BENWU, Departmentof RangelandEcologyand Management,Texas A&MUniversity,College Station,TX 77843, USA
Abstract: Although weather variables are known to influence quail abundance in some habitats, most studies
have addressed only limited geographic areas and indices to weather conditions. The few replicated studies
addressed relatively similar climate zones. We used 21 years (1978-98) of quail abundance data collected by
the Texas Parks and Wildlife Department (TPWD) biologists to address the relationship between both simple
precipitation and Palmer drought indices and Northern Bobwhite (Colinus virginianus) and Scaled quail (Callipepla squamata) abundance in 6 ecological regions of Texas. Three 12-month Palmer indices were more
highly correlated with changes in Northern Bobwhite abundance in the South Texas Plains ecological region
than was raw precipitation alone. The 12-month Modified Palmer Drought Severity Index (PMDI) was correlated (r, > 0.78, P ? 0.001) with the mean number of Northern Bobwhites visually observed per survey
route in the Rolling and South Texas Plains ecological regions, while a 12-month, raw precipitation index was
correlated (r, = 0.64, P = 0.002) with Northern Bobwhite abundance in only the South Texas Plains. The
PMDI and raw precipitation were correlated (r, > 0.67, P 0.001and r, 0.57, P - 0.007, respectively) with
- Plateau, South Texas Plains, and
the mean number Scaled Quail observed per survey route - in the Edwards
Trans-Pecos Mountains and Basins ecological regions. There was no relationship (P - 0.437) between changes
in quail abundance and the PMDI or raw precipitation in the Gulf Prairies and Marshes physiographic region,
where precipitation was relatively high. The monthly PMDI was a better indicator of changes in both northern
bobwhite and Scaled Quail abundance among years than was monthly precipitation alone. Both monthly and
12-month precipitation-based weather indices were more correlated with changes in Northern Bobwhite and
scaled quail abundance among years in relatively dry as opposed to wet ecological regions. Our approach
should help wildlife biologists and managers better account for annual variability in quail productivity in semiarid environments so that long-term populations trends can be better elucidated.
JOURNALOF WILDLIFE
MANAGEMENT
65(1):10-18
Key words: Callipepla squamata, Colinus virginianus, drought, Northern Bobwhite, Palmer Drought Severity
Index, precipitation, abundance, climate, Scaled quail, Texas, weather.
Rainfall and moisture availability are among
the most influential forces influencing terrestrial
ecosystems (Clarke 1954:109, Odum 1963:70,
Krebs 1972:70) and avian reproduction (Marshall 1959). Relationships between weather and
population parameters such as nesting success
and recruitment have been examined for a
number of ground-nesting species (Beasom and
Pattee 1980, Peterson and Silvy 1994, Sheaffer
and Malecki 1996). Both California quail (Cal-
lipepla californica; Francis 1967, 1970; Botsford
et al. 1988) and Gambel's quail (C. gambelii;
Swank and Gallizioli 1954, Gullion 1960, Heffelfinger et al. 1999) recruitment and abundance were dependent on precipitation and
other weather conditions.
For Northern Bobwhite and Scaled quail,
weather conditions have contributed to shortterm and possibly long-term (Schemnitz 1993)
population trends. Payne and Bryant (1994:270)
considered the "boom or bust" relationship between quail abundance and weather conditions
a "classic example" of wildlife response to
drought. In high rainfall areas of the Southeast,
Stoddard (1931:201) and Rosene (1969:145)
proposed that heavy rainfall during the nesting
and brooding season resulted in poor northern
I Present Address:
Department of Fisheries and
Wildlife Sciences, Virginia Polytechnic Institute and
State University, Blacksburg, VA 24061, USA.
2 E-mail: [email protected]
3present Address: Department of Wildlife and
Fisheries Sciences, Texas A&M University, College
Station, TX 77843, USA.
10
J. Wildl. Manage. 65(1):2001
QUAILABUNDANCEAND WEATHER * Bridges et al.
bobwhite production, but argued drought also
might be detrimental. Durell (1957), Murray
(1958), and Speake and Haugen (1960) found
production and recruitment of southeastern
northern bobwhites was highest after a wet
summer breeding season. Guthery et al. (1988)
concluded that aridity influenced the effective
reproductive season for northern bobwhites in
south Texas. Similarly, Rice et al. (1993) found
that bobwhite abundance and weather variables
were more strongly correlated in arid southern,
as opposed to less arid northern or coastal, Texas.
The relationship between Scaled quail and
weather conditions also has been examined.
Schemnitz (1961) noted that scaled quail abundance in Oklahoma remained high during what
he considered to be drought years. However,
Wallmo and Uzell (1958) and Campbell (1968)
found positive relationships between precipitation and Scaled quail abundance in western
Texas and New Mexico, respectively. Schemnitz
(1994), in his review of the scaled quail literature, called for further research into the relationship between weather variables and scaled
quail recruitment.
The mechanisms by which drought and other
climatic conditions influence quail numbers
have been the subject of much conjecture.
Many individuals assumed that Northern bobwhite must drink water daily for survival. In his
examination of northern bobwhite populations
in the humid southeastern United States, Stoddard (1931:500) concluded that sufficient water
probably was available from dew and food.
Guthery (1986:17) proposed that surface water
might limit quail populations in more arid regions such as southern Texas and might be especially important to laying females (Koerth
and Guthery 1990). Subsequent analyses, however, failed to provide conclusive evidence of
this relationship (Guthery and Koerth 1992).
Precipitation also might affect quail abundance
by chilling exposed chicks or destroying nests
(Stoddard 1931:201), improving habitat conditions in overgrazed pastures (Cantu and Everett
1982), influencing vitamin A (Hungerford 1964)
and-or phosphorus availability (Cain et al.
1982), concentrating phytoestrogens (Leopold
et al. 1976, Cain et al. 1987), altering available
vegetation (Campbell et al. 1973), influencing
insect availability (Roseberry and Klimstra
1984:112), and changing corticosterone levels
11
through water stress (Cain and Lien 1985, Giuliano et al. 1995).
Most previous studies used raw precipitation
to predict quail response to weather conditions.
A few more recent studies used subsets of
Thornthwaite's (1948) evapotranspiration index.
Rice et al. (1993) stated that precipitation, due
to regional differences in other weather variables (temperature, wind, and humidity), might
not adequately represent the impact of weather
on quail abundance. Furthermore, Risser et al.
(1981:3) concluded that grassland ecosystems
were controlled by complex relationships between temperature regimes and precipitationevaporation ratios, not just raw precipitation,
evaporation, or temperature.
Climatologists and meteorologists rely on the
Palmer (1965) family of drought indices for assessing ecosystem-level moisture conditions (Alley 1984, Heddinghaus et al. 1987, Guttman et
al. 1992). Palmer (1965) designed the Palmer
Drought Severity Index to measure the departure from normal regional moisture supply. The
Palmer indices use precipitation, temperature,
Thornthwaite's (1948) evapotranspiration index,
runoff, soil recharge, and average regional
weather conditions to quantitatively evaluate
the long-term impacts of departures from normal weather conditions on an ecosystem (Palmer 1965, Alley 1984, Heddinghaus and Sabol
1991, http://www.ncdc.noaa.gov). The Palmer
indices are calibrated using long-term weather
averages for each climate region in an attempt
to make regional weather conditions comparable in both space and time. Although climatologists recognize that spatial calibration imperfections still exist, a value of -3.00 in Kentucky
in July theoretically should represent an equivalent departure from average weather conditions as -3.00 in Nebraska in January (Guttman
et al. 1992). The Palmer (1965) indices were
developed specifically for semiarid and dry subhumid climates (Guttman et al. 1992) similar to
those found over much of the range of North
American quails.
Wildlife ecologists have made little use of
these indices, although Sorenson et al. (1998)
found the Palmer Drought Severity Index was
correlated with breeding duck abundance in the
northern Great Plains. The more comprehensive Palmer suite of weather indices might better represent factors controlling grassland ecosystems, and consequently quail populations,
12
QUAILABUNDANCEAND WEATHER * Bridges et al.
than precipitation alone. No one has evaluated
these indices in this context.
In recent decades, nearly range-wide declines
in both bobwhite (Brennan 1991, Church et al.
1993, Brady et al. 1998) and Scaled quail
(Church et al. 1993) abundance, and concern
over possible global climate change (Gates
1993, Bright 1997, Sorenson et al. 1998), have
highlighted the importance of understanding
quail-weather relationships. Although numerous studies have addressed quail abundance and
weather, few were conducted at spatial scales
sufficiently broad to address multiple climate
zones. Similarly, weather indices such as the
Palmer Drought Severity Index have not been
evaluated. Our objectives were to (1) assess the
relationship between weather and abundance of
bobwhite and scaled quail at the ecological region scale in Texas, (2) compare the relative significance of the quail-weather relationship in
different ecological regions, and (3) explore the
relationships between Palmer (1965) drought
indices and changes in quail abundance in 6
Texas physiographic regions. Specifically, we hypothesized that there would be a stronger positive relationship between weather indices and
quail abundance in more arid as opposed to
comparatively wet ecological regions and that
the more comprehensive Palmer drought indices would be more highly correlated with
changes in quail abundance among years than
raw precipitation alone.
J. Wildl. Manage. 65(1):2001
A
IoI
3.0J
1%1
(50%)
STUDYAREAS
The influence of weather on northern bobwhite and Scaled quail abundance was evaluated in all Texas ecological regions (Gould 1975;
Fig. 1A) where TPWD biologists collected quail
abundance data for 1 or both species throughout the 21-year (1978-98) period. Unfortunately, insufficient quail abundance data were available for the Pineywoods, Blackland Prairies,
Post Oak Savannah, and High Plains physiographic regions. Further, because scaled quail
have nearly disappeared from much of the Rolling Plains, insufficient data were available for
time-series analysis for this species. For bobwhites, analyses were conducted for the Gulf
Prairies and Marshes, Cross Timbers and Prairies, Edwards Plateau, Rolling Plains, and South
Texas Plains (Fig. 1A). For Scaled quail, we
evaluated the Edwards Plateau, South Texas
Plains, and Trans-Pecos Mountains and Basins
ecological areas. Mean annual precipitation
.
I
Fig. 1. Ecological(A; Gould1975) and climatological(B) regions (NationalClimateData Center)of Texas, includingrelative aridity(%)(P/PE, where P = average annualprecipitation and PE = average potentialevapotranspiration;
Muller
and Faiers 1995). Names of ecological regions and, where
different,climatologicalregionsare as follows:HighPlains(1),
RollingPlains (2), Cross Timbersand Prairies;NorthCentral
(3), Pineywoods;East Central(4), Trans-Pecos, Mountains
and Basins (5), EdwardsPlateau (6), Post Oak Savannah;
SouthCentral(7), GulfPrairiesand Marshes;UpperCoast (8),
South Texas Plains; Southern (9), Lower Valley (10), and
BlacklandPrairies(11).
across these regions typically ranges from 20 to
125 cm, with considerable seasonal variation
(Carr 1969).
METHODS
Data
We used data compiled by TPWD from 1978
through 1998 to calculate regional quail abundance indices. During the first 2 weeks of Au-
J. Wildl. Manage. 65(1):2001
QUAILABUNDANCEAND WEATHER* Bridges et al.
gust each year, TPWD biologists ran a series of
32.2-km census routes randomly selected and
permanently placed throughout the ecological
regions of Texas. Observations began either 1hr before sunset or at sunrise when weather
met a predetermined set of conditions. Observers drove at 32 km/hr and recorded the number
of quail of each species visually observed (divided into singles, pairs, and coveys) and the approximate age of quail based on body size at
1.6-km intervals (Peterson and Perez 2000). We
calculated our abundance indices as the mean
number of quail seen per route per ecological
region (Fig. 1A) during a given year.
The western extent of northern bobwhite and
eastern extent of Scaled quail ranges fall within
the Rolling Plains, Edwards Plateau, and South
Texas Plains ecological regions of Texas (Reid
1977). Therefore, all routes in these regions are
not within the range of both species. If either
Northern Bobwhite or Scaled quail had never
been observed on a given route since it inception (1978), that route was not considered within the range of that species and was excluded
when calculating mean abundance per ecological area. In this way, mean values were not artificially low in ecological areas at the fringe of
a given species' range, thus allowing these values to be compared across physiographic regions.
We conducted power analyses (MINITAB
1998) to ensure that biologically significant fluctuations in mean abundance could be detected.
These analyses revealed that a doubling in
mean quail abundance (100%) could be detected in all ecological regions at the 1-B - 0.80
probability level (a = 0.05).
Weather data were acquired from the National Oceanic and Atmospheric .Administration's (NOAA) National Climate Data Center
(NCDC). These data included raw precipitation, Palmer Z Index (ZNDX), Palmer Hydrological Drought Index (PHDI), Palmer Drought
Severity Index (PDSI), and Modified Palmer
Drought Severity Index (PMDI) (http://
www.ncdc.noaa.gov). Numerical representations of weather conditions, as calculated
monthly by NCDC, were acquired for the climatological regions of Texas. Climatological regions, while similar, did not perfectly match the
ecological regions of Texas (Fig. 1). Climatological regions 2, 3, 5, 6, 8, and 9 were used for
analyses with the Rolling Plains, Cross Timbers
and Prairies, Trans-Pecos Mountains and Ba-
13
sins, Edwards Plateau, Gulf Prairies and Marshes, and South Texas Plains ecological regions,
respectively. Because we used single values to
represent weather conditions over broad spatial
extents, slight differences in boundaries were
not considered important for our purposes. After all, the boundaries of neither classification
represent clearly delineated features on the
ground.
Analyses
Because trends in both quail abundance and
weather data could confound correlative analyses, we used time-series regression (MINITAB
1998) to detrend both weather and quail abundance data. Because the residuals were not always normally distributed, we used Spearman's
rank order correlation (MINITAB 1998) for all
analyses. Tests were considered significant at
the P < 0.01 level.
We first calculated a regional aridity index (P/
PE, where P = average annual precipitation
and PE = average potential evapotranspiration)
for each NOAA climatological region of Texas
(Muller and Faiers 1995). These values were
used later to assess whether data were consistent with the hypothesis that the weather indices evaluated below should be more strongly
related to changes in quail abundance in comparatively dry versus wet regions.
We then tested the hypotheses that Palmer
drought indices (ZNDX, PHDI, PDSI, PMDI)
could account for more variation in quail abundance among years in the South Texas Plains
than raw precipitation alone. We chose this ecological region primarily because both northern
bobwhites and scaled quail occurred there and
no long-term trends in the abundance of either
species were observed during the 21-year survey period. We developed 12-month Palmer indices by summing the individual months (SepAug) preceding the annual TPWD quail abundance survey. We also developed a 12-month
raw precipitation index in the same manner.
The PHDI, PDSI, and PMDI were designed to
assess long-term dryness or wetness of a region,
so individual monthly values are dependent to
varying degrees on preceding months. The fact
that some information was duplicated does not
matter for our purposes, because our 12months indices were used simply as metrics for
evaluating quail response, rather than as indicators of wetness or dryness. The degree of correlation between each of the 12-month Palmer
14
QUAIL ABUNDANCE AND WEATHER o Bridges et al.
Table 1. Correlations(r,;P - 0.0002) between 12-monthsums
of raw precipitationand the Palmer Z, Palmer Hydrological
Drought, Palmer Drought Severity, and Modified Palmer
DroughtSeverity Indices and northernbobwhiteand scaled
quailabundance in the South Texas Plains ecological region
(Gould1975), 1978-98. Alldata were detrendedover years.
Northern bob- Scaled
white
quail
Index
0.64
Precipitation
PalmerZ Index
0.67
Palmer HydrologicalDrought Index
0.87
Palmer Drought SeverityIndex
0.80
ModifiedPalmerDroughtSeverityIndex 0.90
0.66
0.70
0.67
0.79
0.73
J. Wildl. Manage.
65(1):2001
areas discussed above. Twelve month PMDI
and precipitation indices were calculated by
summing the 12 months (Sept-Aug) prior to
each year's quail survey. Finally, to further evaluate this hypothesis, we also determined the degree of correlation between individual monthly
values of both the PMDI and raw precipitation
and the annual mean number of northern bobwhites and scaled quail per route for each ecological region.
RESULTS
and raw precipitation indices and variations in
bobwhite and scaled quail abundance were then
calculated.
The ZNDX was intended to examine shortterm weather conditions, while the PHDI was
designed primarily to quantify the impacts of
weather on the hydrological cycle (e.g. stream
flow and water storage; Heddinghaus and Sabol
1991). Palmer (1965) created the PDSI to
quantify the long-term impacts of departures
from normal regional and seasonal moisture
supply on a system. In 1989, climatologists
modified the PDSI (creating the PMDI) to better represent real-time conditions and transitional periods (Heddinghaus and Sabol 1991).
Because the ZNDX, PHDI, PDSI, and PMDI
are closely related to each other, and for presentational simplicity, we chose a single Palmer
drought index for all remaining analyses. We selected the PMDI because it was designed to
quantify long-term weather impacts and better
represent real-time and transitional periods.
We next tested the hypothesis that the 12month PMDI could account for more variation
in quail abundance among years than raw precipitation alone in each of the 6 Texas ecological
Conditions were progressively more arid
from east to south and west in Texas (Fig. IB).
These relative aridity values serve as the context
for the following results. All 12-month Palmer
indices (PDSI, PMDI, PZI, PHDI) were correlated with northern bobwhite and scaled quail
abundance in the South Texas Plains ecological
region (Table 1). For northern bobwhites, these
correlations were somewhat greater than those
obtained for the more traditional raw precipitation index.
Twelve-Month
PMDIand Precipitation
The 12-month PMDI indices were correlated
with the mean number of northern bobwhites
observed per survey route in both the Rolling
and South Texas Plains ecological regions (Table
2). The 12-month precipitation index was correlated with annual mean northern bobwhite
abundance only in the South Texas Plains. Neither the 12-month PMDI nor the 12-month
precipitation indices were correlated with mean
northern bobwhite abundance in the increasingly moist (Fig. 1) Edwards Plateau, Cross
Timbers and Prairies, and Gulf Prairies and
Marshes (Table 2).
Scaled quail abundance in the Edwards Plateau, South Texas Plains, and Trans-Pecos
Table2. Correlationsbetween the 12-monthsums of rawprecipitation
(Precip)and the ModifiedPalmerDroughtSeverityIndices
(PMDI)and northernbobwhiteand scaled quailabundanceby Texas ecological region(Gould1975), 1978-98 (listedin order
of increasingaridity(GPM = Gulf Prairiesand Marshes,CTP = Cross Timbersand Prairies,EP = EdwardsPlateau, RP =
RollingPlains, STP = South Texas Plains,and TP = Trans-PecosMountainsand Basins). Alldata were detrendedoveryears.
Northern bobwhite
PMDI
Scaled quail
PMDI
Precip
Region
r,
P
rs
rP
P
GPM
CTP
EP
RP
STP
TP
0.01
0.54
0.52
0.78
0.90
0.960
0.012
0.016
<0.001
<0.001
0.17
0.20
0.29
0.26
0.64
0.471
0.385
0.197
0.256
0.002
Precip
P
rs
P
0.69
0.001
0.57
0.007
0.75
0.67
<0.001
0.001
0.66
0.67
0.001
0.001
J. Wildl.
Manage. 65(1):2001
QUAILABUNDANCEAND WEATHER* Bridges et al.
Mountains and Basins ecological regions were
correlated with both the 12-month PMDI and
precipitation indices (Table 2). These are
among the most arid regions of Texas (Fig. 1).
MonthlyPMDIand Precipitation
The Northern bobwhite was the only species
found in the wettest 2 ecological regions evaluated (Fig. 1). No individual monthly correlations (P range: 0.360-0.893) between PMDI
and quail abundance were documented in the
Gulf Prairies and Marshes ecological region.
Four monthly PMDIs (Nov-Feb) were correlated (rs - 0.57) with Northern bobwhite abundance in the Cross Timbers and Prairies ecological region with November (rs = 0.66) exhibiting the greatest correlation. Monthly precipitation values were not correlated (P range:
0.120-0.960) with quail abundance in either
ecological region.
Quail abundance in the more arid (Fig. 1)
Edwards Plateau and Rolling Plains ecological
regions showed a stronger relationship with
monthly weather indices. Northern bobwhite
abundance in the Edwards Plateau was correlated (rs > 0.59) with the PMDI during 3
months (Sep-Nov), with the strongest correlation coming in September (rs = 0.70). Rolling
Plains bobwhite abundance was correlated (rs >0.56) with 8 individual months (Sep-Feb, Apr,
Jun), with November (rs = 0.70) being the most
correlated. In the Edwards Plateau, scaled quail
abundance was correlated (rs - 0.62) with 5
monthly PMDIs (Dec-Mar, Jun), with February (rs = 0.69) exhibiting the highest correlation. Again, no monthly raw precipitation values
were correlated with bobwhite (P range: 0.0790.841) abundance. Scaled quail abundance was
correlated with precipitation in the Edwards
Plateau during only June (r, = 0.66).
Relationships between quail abundance and
weather were even greater in the arid South
Texas Plains (Fig. 1). Ten monthly PMDIs
(Oct-Jul) were correlated (rs > 0.56) with
northern bobwhite abundance, with April (r, =
0.74) exhibiting the strongest relationship (FebMay were nearly identical). Nine monthly
PMDIs (Dec-Aug) were correlated (rs - 0.56)
with Scaled quail abundance, with February (r,
= 0.81) accounting for the most variability. The
February raw precipitation index was correlated
with both northern bobwhite (rs = 0.63) and
Scaled quail (rs = 0.78) abundance.
Scaled quail were the only species surveyed
15
in the most arid ecological region of Texas, the
Trans-Pecos Mountains and Basins (Fig. 1).
Eight monthly PMDIs (Oct-Jan, Apr-Jul) were
correlated (rs > 0.56) with scaled quail abundance. The June PMDI exhibited the strongest
relationship (rs = 0.75). Only September and
November raw precipitation were correlated (rs
= 0.73 and 0.61, respectively) with scaled quail
abundance.
DISCUSSION
The 12-month PMDI index accounted for
more variability in Northern Bobwhite abundance in the Texas ecological regions we evaluated than did the 12-month raw precipitation
index. Not surprisingly, the other closely related
Palmer indices performed similarly where evaluated. In most cases, more individual months
were correlated, and monthly PMDIs accounted for more variability in both Northern Bobwhite and Scaled quail abundance among years
than did monthly raw precipitation alone.
Therefore, at the ecological region scale in Texas, our results are consistent with the hypothesis
that PMDI is more closely associated with
changes in quail abundance than raw precipitation alone. It also is clear that both the 12month and monthly PMDIs, as well as the analogous raw precipitation indices, were more
closely related to annual changes in quail abundance in relatively arid as opposed to wet regions of Texas (Fig. 1). Therefore, these data
are consistent with the hypothesis that precipitation-based weather variables are better predictors of changes in northern bobwhite and
scaled quail abundance among years in dry as
opposed to wet ecological regions.
Guthery (1986:17) hypothesized that Northern Bobwhite populations in the relatively arid
western portions of their range might be more
dependent on rainfall and other weather conditions than eastern populations. Numerous researchers working at relatively fine spatial scales
found that wet years were associated with increased abundance of Northern Bobwhite
(Lehmann 1946, Kiel 1976, Guthery et al.
1988) and scaled quail (Wallmo and Uzzell
1958, Campbell 1968, Campbell et al. 1973) in
semiarid western locations. Similarly, Rice et
al. (1993) found stronger correlations between
Northern Bobwhite abundance and weather in
southern than in northern or coastal Texas.
Roseberry and Klimstra (1984:111), however,
found no sip'nificant relationship between
16
QUAILABUNDANCEAND WEATHER * Bridges et al.
weather and northern bobwhite production in
Illinois where precipitation is relatively high.
These studies are consistent with our results
even though our analyses were conducted at a
much broader spatial scale.
Conversely, Stoddard (1931:201) and Rosene
(1969:145) maintained that heavy rainfall events
during the breeding season could reduce
Northern Bobwhite recruitment. They provided
no empirical support for this hypothesis.
Schemnitz (1961) noted that Scaled quail abundance remained high during what he considered a drought period. He later (1993) proposed that above average precipitation might
actually be responsible for long-term declines
in scaled quail abundance observed in the
Oklahoma panhandle during the 1980s. He tested neither hypothesis. Giuliano and Lutz
(1993), using Christmas Bird Count data, concluded that precipitation did not limit Northern
bobwhite abundance and was negatively correlated with that of scaled quail in southern Texas.
It is probable, however, that an August survey
conducted by wildlife biologists provides a better estimate of quail production in Texas than
does the Christmas Bird Count.
It is likely that monthly PMDI was more
highly correlated with changes in quail abundance than raw precipitation because it more
accurately quantified the effects of weather on
regional vegetational communities (Palmer
1965). Because native plants are adapted to
weather conditions in a given region (Peoples
et al. 1994), an index based on average regional
weather conditions should better predict vegetational response than one based on raw precipitation or potential evaporation alone. Similarly,
inclusion of soil moisture improves the ability
to predict vegetational response. Moreover, limiting weather variables for the grassland ecosystems inhabited by quail cannot be adequately
quantified by simple measures such as precipitation, temperature, and evaporation, but are
controlled by complex interactions among precipitation, evaporation, and temperature (Risser
et al. 1981:3).
Because the PMDI and other Palmer indices
better quantify the effects of weather on regional vegetation communities than does raw
precipitation, temperature, or even evapotranspiration alone, it is likely that our approach
could productively be adapted for other
ground-nesting avian species endemic to semiarid grasslands. Because weather variables can
J. Wildl. Manage. 65(1):2001
markedly alter production and recruitment, particularly of more r-selected species, accounting
for this variability in both conceptual and mathematical models is important. For example, the
potential listing of the lesser prairie-chicken
(Tympanuchus pallidicinctus) as threatened under the Endangered Species Act demonstrates
the importance of being able to account for annual variability in density caused by weather so
that long-term trends in abundance can be better elucidated. This study illustrates a productive way to account for variability in reproductive productivity among years for 2 species of
ground nesting birds inhabiting semiarid rangelands.
ACKNOWLEDGMENTS
The Rob and Bessie Welder Wildlife Foundation, TPWD, and Texas A&M University provided support for this project. We thank TPWD
for collecting and providing the quail abundance data and M. C. Frisbie for assisting with
data manipulation. We also acknowledge the
NCDC and NOAA for the weather indices used
in our analyses. Lastly, we thank 3 anonymous
reviewers for their constructive comments.
LITERATURE
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Received 21 September 1999.
Accepted 5 June 2000.
Associate Editor: Dabbert.