POPULATION-DYNAMICS OF THE GREY PARTRIDGE PERDIX-PERDIX 1793-1993 - MONITORING, MODELING AND MANAGEMENT

Citation
Gr. Potts et Nj. Aebischer, POPULATION-DYNAMICS OF THE GREY PARTRIDGE PERDIX-PERDIX 1793-1993 - MONITORING, MODELING AND MANAGEMENT, Ibis, 137, 1995, pp. 29-37
Citations number
29
Categorie Soggetti
Ornithology
Journal title
IbisACNP
ISSN journal
00191019
Volume
137
Year of publication
1995
Supplement
1
Pages
29 - 37
Database
ISI
SICI code
0019-1019(1995)137:<29:POTGPP>2.0.ZU;2-7
Abstract
The longest available bag record of Grey Partridges Perdix perdix in G reat Britain (1793-1993) reveals a collapse of stocks after 1952 despi te considerable annual variation. The annual fluctuations were attribu table largely to annual variations in chick survival rate. The Game Co nservancy Trust's National Game Census revealed that chick survival ra tes averaged 49% before the introduction of herbicides and 32% once th eir use became widespread. On a study area in Sussex, where spring den sity declined from around 21 pairs per km(2) in 1968 to under four pai rs per km(2) in 1993, annual chick survival rates averaged 28% with no demonstrable trend, The annual over-winter ''survival'' rates in the area improved during 1968-1993, whereas brood production rates decline d, Simulation modelling showed that a reduction in chick survival rate from 49% to 32% had little effect on spring stocks as long as nest pr edation was controlled but that stocks collapsed when nest predation c ontrol was relaxed. The effect of such a change in chick survival rate on population status was investigated by reference to 36 other studie s in the literature. Amongst 20 studied populations which were stable, adjusting mean chick survival rates downwards produced demographic pa rameters characteristic of declining populations in all but two cases, Conversely, adjusting chick survival rates upwards for 16 declining p opulations made all but two stable. Diagnosing and remedying the cause s of population change require a testable understanding of density-dep endent factors and compensatory processes, best approached by a combin ation of monitoring, modelling and management.