1 Many plant species are currently restricted to small and isolated populations as a result of habitat destruction and fragmentation. Lack of sufficient data often leads to spatial variation being substituted for temporal variation in models to evaluate management options, but variation in population growth rate () between sites or over years may be caused by variation in different life history components. 2 We studied the demography of three coexisting and related perennial herbs (the longlived perennial Succisa pratensis, the shorter-lived Hypochaeris radicata and the longlived, but more clonal Centaurea jacea ) in the same plots over 4 years (1999¿2003). 3 Life table response experiment analysis revealed that temporal and spatial variation in the life history components of S. pratensis and H. radicata were qualitatively different: variation in fecundity contributed most to variation in between sites, but variation in growth contributed most to variation between years. 4 In years with a below average, most life history components of S. pratensis and H. radicata had lower transition probabilities, whereas the reasons for low population growth differed between the three poor sites. All major life history components of S. pratensis had lower probabilities in the most productive of these sites, but in the other two, negative contributions from some components (fecundity or growth) were partly compensated for by positive contributions from others (growth or stasis). 5 Centaurea jacea showed a different pattern: in poor years, negative contributions from some life history components were buffered by positive contributions from other components; however, this buffering did not occur in poor sites. 6 Our analysis shows that the population dynamics of perennial plants may respond differently to temporal and spatial variation in environmental conditions. Moreover, co-occurring species with similar life histories responded differently to the same spatiotemporal variation. We conclude that temporal and spatial dynamics cannot readily be interchanged in population viability analyses and management studies, as such substitution may lead to incorrect projections of a species¿ population dynamics in time. Key-words : buffering of variation, demography, life history components, population growth rate, variation decomposition.
- projection matrices
- viability analyses