Differential effects of abandonment on the demography of the grassland perennial Succisa pratensis
2014 (English)In: Population Ecology, ISSN 1438-3896, E-ISSN 1438-390X, Vol. 56, no 1, 151-160 p.Article in journal (Refereed) Published
Abandonment of traditional land-use practices can have strong effects on the abundance of species occurring in agricultural landscapes. However, the precise mechanisms by which individual performance and population dynamics are affected are still poorly understood. To assess how abandonment affects population dynamics of Succisa pratensis we used data from a 4-year field study in both abandoned and traditionally grazed areas in moist and mesic habitats to parameterize integral projection models. Abandoned populations had a lower long-term stochastic population growth rate (lambda (S) = 0.90) than traditionally managed populations (lambda (S) = 1.08), while lambda (S) did not differ between habitat types. The effect of abandonment differed significantly between years and had opposed effects on different vital rates. Individuals in abandoned populations experienced higher mortality rates and lower seedling establishment, but had higher growth rates and produced more flower heads per plant. Population viability analyses, based on a population survey of the whole study area in combination with our demographic models, showed that 32 % of the populations face a high risk of extinction (> 80 %) within 20 years. These results suggest that immediate changes in management are needed to avoid extinctions and further declines in population sizes. Stochastic elasticity analyses and stochastic life table response experiments indicated that management strategies would be most effective if they increase survival of small plants as well as seedling establishment, while maintaining a high seed production. This may be achieved by varying the grazing intensity between years or excluding grazers when plants are flowering.
Place, publisher, year, edition, pages
2014. Vol. 56, no 1, 151-160 p.
Grazing, Integral projection models (IPM), Management, Population dynamics, Population viability, Stochasticity
Environmental Sciences Ecology
IdentifiersURN: urn:nbn:se:su:diva-99875DOI: 10.1007/s10144-013-0400-7ISI: 000328852000016OAI: oai:DiVA.org:su-99875DiVA: diva2:690590
EU, EVK2-CT-1999-00004; University of Amsterdam 2014-01-242014-01-202014-01-24Bibliographically approved