Disentangling the effects of land use, shrub cover and climate on the invasion speed of native and introduced pines in grasslands

Abstract

AbstractAims To determine how changes in land use, climate and shrub cover affect the invasion dynamics of native (Pinus sylvestris L.) and introduced (Pinus nigra Arn. subsp. nigra) pines in grasslands. To analyse how these factors interact and affect seedling recruitment, a bottleneck in the lifecycle of many trees. Such information is required to manage the dynamics of these species.Location Grands Causses, calcareous plateaus (Southern France).Methods We used both published and unpublished demographic and dispersal data to assess population growth and invasion speed of invading pines. A demographic and spatially explicit model, which included density dependence and stochasticity in dispersal, demography and environment, was run for different scenarios of sheep grazing pressure (nil, extensive or intensive), shrub cover (0, 10 or 20%) and drought frequency (past‐to‐present or future). For each scenario, population growth rate, invasion speed and elasticity of invasion speed to each demographic and dispersal parameter were computed.Results Grazing was the main factor for limiting invasion speed. Shrub cover reduced tree spread under nil or extensive grazing pressure, but increased it under intensive grazing pressure. Although dry years led to nil seedling establishment rates, an increase in their frequency had surprisingly few effects on pine invasion speed. This last result remained unchanged when very dry years, inducing seedling, but also sapling mortality were introduced. In most environmental conditions, population growth rate and invasion speed were higher for the introduced than for the native pine. Elasticity analysis highlighted the importance of demographic parameters on invasion speed, notably adult and sapling survival.Main conclusion Tree invasion speed may rely at least as much on human activities, like sheep grazing, tree cutting and non‐native trees introduction, as on changes in climate factors. Therefore, human activities need to be explicitly taken into account in the prediction and management of tree dynamics.