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Scaled quail {Callipepla squamata ) is an upland species that has declined in areas of historical distribution in Texas . Potential causes for the present decline have been attributed to precipitation and changes in landscape characteristics . The effects of long -term landscape modification , precipitation variation , and scaled quail populations were evaluated using a Geographic Information System (GIS ) . Three databases were included in the construction of the GIS . The first database included records for precipitation for the state of Texas from 1968 through 1997 . The second database consisted of Multispectral Scanner (MSS ) satellite images for the state of Texas obtained during 1973 , 1986 , and 1991 to determine land use and land cover changes . Finally , the third database consisted of annual records for scaled quail population in Texas from 1968 through 1997 . The objective of this project was to evaluate the use of broad -scale data to describe local reduction of scaled quail densities in Texas due to (1 ) changes in suitable habitat ; (2 ) temporal precipitation variation ; and (3 ) the combined effect of long -term habitat modifications and temporal climatic variation .
The temporal distribution of precipitation was studied for two main rainy seasons , corresponding to the months of April -June (first rainy season ) and July -September (second rainy season ) . Temporal precipitation variability and scaled quail population trends were analyzed using cross -spectral analysis for time series to determine whether or not these series were correlated . Scaled quail data were obtained from Breeding Bird Survey records for the 1968 -1997 period . Long -linear models were used to determine scaled quail population trends at individual Breeding Bird Survey routes , ecoregions , and the area of scaled quail distribution in Texas . Two ecoregions were not included in the analysis due to the lack of data . A landscape gradient including rangelands , cultivated lands , water bodies , and urban areas was created to determine changes in suitable habitat during 1973 , 1986 , and 1991 . Scaled quail population densities were compared at state , ecoregion , and Breeding Bird Survey route .
Analysis of the temporal distribution of climatic parameters suggested the presence of annual trends plus lag -times that varied from 2 to 11 years ; however , most sites presented periods ranging between 2 to 3 years . The use of cross -spectral analysis suggested that scaled quail populations in the Basin and Range and the Rolling Plains ecoregions were cross -correlated with precipitation . The Rio Grande Plain and the Texas High Plains ecoregions did not present strong correlations between scaled quail and either rainy season .
Multiple regression indicated that changes in precipitation explained changes in scaled quail for ecoregions were the species is distributed ; however , only the Basin and Range ecoregion presented statistically significant slopes . The combined effect of precipitation and vegetation did not explain changes in scaled quail populations in the Texas High Plains ecoregion . The combination of vegetation and precipitation influenced scaled quail only in the Rolling Plains but the slopes were not statistically significant .
The lack of complete scaled quail records presented a big problem in the analysis of the population trends for the complete distributional range of the species . However , it provided a potential tool to determine changes at the ecoregion level . To develop state - wide management plans for scaled quail populations in Texas , the first step was to develop complete data sets .
Scaled quail populations generally have declined in the past 3 decades . This negative trend may have been influenced by the combination of the temporal and spatial distribution of climatic parameters and habitat modification , however the lack of a strong data set may weaken results making them inconclusive and contradictory . The methodology used in this research provided alternatives to handle missing values and the presence of potential lag -effects in the data . These techniques in combination with more complete databases may provide , in the future better estimations of the relationships between scaled quail and long -term habitat modifications at different scales . Also the use of GIS allowed the integration of large databases to aid in the analysis of potential causes for scaled quail decline in the state of Texas . This approach may also provide the tools for management of other species . |
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