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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 Stable URL: http://www.jstor.org/stable/3803270. Accessed: 31/01/2012 19:46 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at. http://www.jstor.org/page/info/about/policies/terms.jsp JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. Allen Press is collaborating with JSTOR to digitize, preserve and extend access to The Journal of Wildlife Management. http://www.jstor.org

DIFFERENTIAL INFLUENCE OF WEATHER ON REGIONAL QUAIL ABUNDANCE IN TEXAS ANDREW S. BRIDGES,1 2 Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX 77843, USA MARKUS J. PETERSON,3 Texas Parks and Wildlife Department, 210 Nagle Hall, Texas A&M University, College Station, TX 77843, USA NOVA J. SILVY, Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX 77843, USA FRED E. SMEINS, Department of Rangeland Ecology and Management, Texas A&M University, College Station, TX 77843, USA X. BEN WU, Department of Rangeland Ecology and Management, Texas A&M University, 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 the mean number Scaled Quail observed per survey route - in the Edwards - Plateau, South Texas Plains, and 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. JOURNAL OF 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- I Present Address: Department of Fisheries and Wildlife Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. 2 E-mail: abridges@vt.edu 3present Address: Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX 77843, USA. 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 10

J. Wildl. Manage. 65(1):2001 QUAIL ABUNDANCE AND WEATHER * Bridges et al. 11 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 bob- white 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, how- ever, 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 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 be- tween 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 sub- humid 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 QUAIL ABUNDANCE AND WEATHER * Bridges et al. J. Wildl. Manage. 65(1):2001 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 re- gion 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. STUDY AREAS 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. Unfortunate- ly, 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 A IoI I. 3.0J 1%1 (50%) Fig. 1. Ecological (A; Gould 1975) and climatological (B) regions (National Climate Data Center) of Texas, including relative aridity (%)(P/PE, where P = average annual precipitation and PE = average potential evapotranspiration; Muller and Faiers 1995). Names of ecological regions and, where different, climatological regions are as follows: High Plains (1), Rolling Plains (2), Cross Timbers and Prairies; North Central (3), Pineywoods; East Central (4), Trans-Pecos, Mountains and Basins (5), Edwards Plateau (6), Post Oak Savannah; South Central (7), Gulf Prairies and Marshes; Upper Coast (8), South Texas Plains; Southern (9), Lower Valley (10), and Blackland Prairies (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 abun- dance indices. During the first 2 weeks of Au-

J. Wildl. Manage. 65(1):2001 QUAIL ABUNDANCE AND WEATHER * Bridges et al. 13 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 1- hr 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 re- gions. 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- 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 al- ways 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 com- paratively 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 sur- vey period. We developed 12-month Palmer indices by summing the individual months (Sep- Aug) preceding the annual TPWD quail abun- dance 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 12- months 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. J. Wildl. Manage. 65(1):2001 Table 1. Correlations (r,; P - 0.0002) between 12-month sums of raw precipitation and the Palmer Z, Palmer Hydrological Drought, Palmer Drought Severity, and Modified Palmer Drought Severity Indices and northern bobwhite and scaled quail abundance in the South Texas Plains ecological region (Gould 1975), 1978-98. All data were detrended over years. Northern bob- Scaled Index white quail Precipitation 0.64 0.66 Palmer Z Index 0.67 0.70 Palmer Hydrological Drought Index 0.87 0.67 Palmer Drought Severity Index 0.80 0.79 Modified Palmer Drought Severity Index 0.90 0.73 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 12- month PMDI could account for more variation in quail abundance among years than raw precipitation alone in each of the 6 Texas ecological 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 de- gree 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 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 PMDI and 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 Table 2. Correlations between the 12-month sums of raw precipitation (Precip) and the Modified Palmer Drought Severity Indices (PMDI) and northern bobwhite and scaled quail abundance by Texas ecological region (Gould 1975), 1978-98 (listed in order of increasing aridity (GPM = Gulf Prairies and Marshes, CTP = Cross Timbers and Prairies, EP = Edwards Plateau, RP = Rolling Plains, STP = South Texas Plains, and TP = Trans-Pecos Mountains and Basins). All data were detrended over years. Northern bobwhite Scaled quail PMDI Precip PMDI Precip Region r, P rs P rp P rs P GPM 0.01 0.960 0.17 0.471 CTP 0.54 0.012 0.20 0.385 EP 0.52 0.016 0.29 0.197 0.69 0.001 0.57 0.007 RP 0.78 <0.001 0.26 0.256 STP 0.90 <0.001 0.64 0.002 0.75 <0.001 0.66 0.001 TP 0.67 0.001 0.67 0.001

J. Wildl. Manage. 65(1):2001 QUAIL ABUNDANCE AND WEATHER * Bridges et al. 15 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). Monthly PMDI and 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 correla- tion. Again, no monthly raw precipitation values were correlated with bobwhite (P range: 0.079-0.841) 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 (Feb- May 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 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 12- month and monthly PMDIs, as well as the analogous raw precipitation indices, were more closely related to annual changes in quail abun- dance 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 QUAIL ABUNDANCE AND WEATHER * Bridges et al. J. Wildl. Manage. 65(1):2001 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 abun- dance 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 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 CITED ALLEY, W. M. 1984. The Palmer Drought Severity Index: limitations and assumptions. Journal of Climate and Applied Meteorology 23:1100-1109. BEASOM, S. L., AND O. H. PATTEE. 1980. The effect of selected climatic variables on wild turkey productivity. Proceedings of the National Wild Turkey Symposium 4:127-135. BOTSFORD, L. W., T. C. WAINWRIGHT, J. T. SMITH, S. MASTRUP, AND D. F. LOTT. 1988. Population dynamics of California quail related to meteorological conditions. Journal of Wildlife Management 52:469-477. BRADY, S. J., C. H. FLATHER, AND K. E. CHURCH. 1998. Range-wide declines of bobwhite (Colinus virginianus): land use patterns and population trends. Gibier Faune Sauvage 15:413-431. BRENNAN, L. A. 1991. How can we reverse the northern bobwhite population decline? Wildlife Society Bulletin 19:544-555. BRIGHT, C. 1997. Tracking the ecology of climate change. Pages 78-94 in L. Starke, editor. State of the world 1997. W W. Norton, New York, New York, USA. CAIN, J. R., S. L. BEASOM, L. O. ROWLAND, AND L. D. ROWE. 1982. The effects of varying dietary phosphorus on breeding Bobwhite. Journal of Wildlife Management 6:1061-1065. ------, AND R. J. LIEN. 1985. A model for drought inhibition of bobwhite quail (Colinus virginianus) reproductive systems. Comparative Biochemistry and Physiology 82A:925-930.

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