When seeing is not believing: Comparative study of various spatial distributions of invasive species

Expansion of non-native plant Flaveria bidentis (L.) Kuntze driven by a range of factors leading to patchy distribution patterns

Given the growing concern over the ecological impacts of non-native species, exploring these species' expansion edge and distribution patterns and their driving factors is important for developing suitable management measures. Flaveria bidentis (L.) Kuntze, a non-native plant that was introduced to China in the 1990s, has spread from southern Hebei Province, where it first took root, to the surrounding regions and has become one of the most notorious invasive weeds in northern China. Based on 15 years (2006-2021) of extensive field investigations, the spatial distribution of sampling and occurrence points were mapped in the recently expanded region of F. bidentis' population. Then, nearest neighbor analysis is used to characterize the spatial pattern differences between samplings and occurrences. An exponential decay function was used to elucidate the driving factors contributing to the presence and absence of F. bidentis. Our results demonstrated an effective random sampling setup, a heterogeneous spatial distribution of F. bidentis, and a multi-regional independent aggregation distribution pattern (p < .01). There were significant spatial correlations between the aggregation areas of plant occurrence points and the locations of roads and construction sand distribution centers. These findings suggest that human activities involving major roads and construction sand distribution centers were driving factors contributing to this long-distance dispersal and spatially discontinuous distribution patterns. The presence of these patchy distribution patterns has important implications for ongoing efforts to manage populations of non-native species.

A computational study of density-dependent individual movement and the formation of population clusters in two-dimensional spatial domains

The patterns of collective behaviour in a population emerging from individual animal movement have long been of interest to ecologists, as has the emergence of heterogeneous patterns among a population. In this paper we will consider these phenomena by using an individual-based modelling approach to simulate a population whose individuals undergo density-dependent movement in 2D spatial domains. We first show that the introduction of density-dependent movement in the form of two parameters, a perception radius and a probability of directed movement, leads to the formation of clusters. We then show that the properties of the clusters and their stability over time are different between populations of Brownian and non-Brownian walkers and are also dependent on the choice of parameters. Finally, we consider the effect of the probability of directed movement on the temporal stability of clusters and show that while clusters formed by Brownian and non-Brownian walkers may have similar properties with certain parameter sets, the spatio-temporal dynamics remain different.