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Full article available at bioRχiv (DOI: 10.1101/2020.02.29.969428) Abstract: Effects of environmental change on a forest understory herb Predicting the effects of human-caused environmental change on biodiversity and ecosystem functioning is one of the most important tasks ecologists face today. A key component of such predictions is to understand how the environment drives population dynamics. However, most previous studies are based on models built on very spatially-limited data. Here, we use demographic and environmental data collected over the entire Swedish distribution range of Actaea spicata, to build models that can be useful for predicting effects of environmental change on this species in its northern range. We collected data at 43 sites between 2017 and 2019. At each site, and established plots to cover 30–50 individuals of different life-cycle stages. We included newly-established individuals in the subsequent years and collected data on individual above-ground size, survival and reproductive output for the two annual transitions. Almost 2600 individuals are included in the study. Furthermore, we collected data on twelve environmental variables describing climate, light availability, soil properties and forest composition. Finally, we tested the significance of each environmental parameter using regression models and built integral projection models (IPMs) to estimate the impact of those variables on the population growth rate (λ) of A. spicata. We present effects of the measure environmental drivers on vital rates and population growth rate. We also present results from simulations, using our models, on effects of changes in climate and other environmental factors and discuss the consequences of environmental change on Actaea spicata’s demography and on the northern distribution of this species.
Poster and supplementary information presented at the fourth conference of the Nordic Society Oikos, 3 - 5 March 2020 in Reykjavík, Iceland (https://www.oikos2020.org).
Integral Projection Model, Population growth rate, Population dynamics, Spatial variation, Environmental drivers, IPM, lambda, Plant demography
Integral Projection Model, Population growth rate, Population dynamics, Spatial variation, Environmental drivers, IPM, lambda, Plant demography
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