Density dependence and spatial heterogeneity limit the population growth rate of invasive pines at the landscape scale

Abstract

Determining population growth across large scales is difficult because it is often impractical to collect data at large scales and over long timespans. Instead, the growth of a population is often only measured at a small, plot-level scale and then extrapolated to derive a mean field estimate. However, this approach is prone to error since it simplifies spatial processes such as the neighbourhood effects of density and dispersal. We present a novel approach that estimates how spatial processes derived from the effects of density and dispersal affect population growth between plot scales and landscape scales. The method is based on a scale transition theory and calculates a transition term to measure the spatial scaling of population growth, which we extend to unstable, expanding populations in order to assess whether landscape-scale population dynamics are different from those estimated at smaller spatial scales. We illustrate this approach using aerial imagery of eight locations in New Zealand experiencing non-native pine invasions. Analyses examined the dynamics at a plot scale (1 ha) and compared this to estimates across entire landscapes (between 24 and 1600 ha), in several cases for more than one time period. We used a Bayesian spatial random effects model to examine population growth and to account for neighbourhood effects and dispersal between plots in a rapidly changing system.We found that the estimates of the scale transition term were typically 10-25% of the mean field estimates, which led to mean field estimates of population growth extrapolated from plots being considerably higher than landscape estimates. The approach we have developed will not only have applications for predicting the populations' growth of invasive species, but also for studies examining the scaling of landscape-scale phenomena.

Partial differential equation models for invasive species spread in the presence of spatial heterogeneity

“… Further details and earlier images of this site can be found in [ 41 ]. Image sourced from the LINZ Data Service and licensed by The Canterbury Aerial Imagery (CAI) consortium for reuse under a CC BY 4.0 license.…”

How to link people, government, and science in effective large-scale management of invasive trees

“…If an invasion is not prevented, early action is the next most effective response, and provides opportunities for local volunteer groups to become involved in control efforts (Figure 3B). Predicting the likely population trajectory of existing invasions is crucial to prioritise control efforts regionally (Sprague et al, 2021). Research from the 'Winning Against Wildings' programme supports this approach, as findings on the impacts and legacies of invasive conifers suggest that even at low densities, conifers can start to alter an ecosystem (Sapsford et al, 2020;Dickie et al, 2022).…”