LONG-TERM POPULATION ANALYSIS OF GRAY PARTRIDGE IN EASTERN WASHINGTON

Citation
Jj. Rotella et al., LONG-TERM POPULATION ANALYSIS OF GRAY PARTRIDGE IN EASTERN WASHINGTON, The Journal of wildlife management, 60(4), 1996, pp. 817-825
Citations number
46
Categorie Soggetti
Ecology,Zoology
ISSN journal
0022541X
Volume
60
Issue
4
Year of publication
1996
Pages
817 - 825
Database
ISI
SICI code
0022-541X(1996)60:4<817:LPAOGP>2.0.ZU;2-8
Abstract
Recent studies reported that gray partridge (Perdix perdix) population s have declined throughout Europe and Asia. Gray partridge on the Palo use Prairie of Washington also have been reported to be in decline. Th erefore, we analyzed densities of gray partridge on the Palouse Prairi e of Washington to determine long-term population trends (1940-92). We also tested for density dependence in recruitment and fall-and-winter mortality rates and attempted to relate annual variation in recruitme nt and mortality to weather and habitat variables. Spring and/or fall estimates of density were available for 33 of 53 years and varied from 1.3 to 23.2 birds/km(2) in the spring and from 0.1 to 28.6 birds/km(2 ) in the fall. The population's return point from 1940 to 1954 was 3.4 5 birds/km(2) versus 6.72 birds/km(2) from 1982 to 1992, indicating th at density was higher in the more recent period. Surprisingly, this re sult contrasts with a series of reports that indicated that the popula tion was in serious decline. We detected density-dependent effects on recruitment rate, fall-and-winter mortality rate, and annual change in population size. Density dependence had the strongest effects on recr uitment rate. Recruitment rate averaged 1.55 (SE = 0.27) but ranged wi dely (0.38-3.38). Fall-and-winter mortality averaged 0.29 (SE = 0.06). We were not able to explain variation in population-growth rate or fa ll-and-winter mortality rate using habitat and/or weather variables (P > 0.11). Under current habitat conditions, density typically will be 6.7 birds/km(2) in the spring and 10.4 birds/km(2) in the fall and can be expected to vary markedly independent of density. By combining ava ilable datasets, we developed a lengthy time series adequate for inves tigating long-term population dynamics. Such an approach may be possib le and informative for other populations.