Do David and Goliath Play the Same Game? Explanation of the Abundance of Rare and Frequent Invasive Alien Plants in Urban Woodlands in Warsaw, Poland

<div><p>Invasive Alien Plants occur in numbers differing by orders of magnitude at subsequent invasion stages. Effective sampling and quantifying niches of rare invasive plants are quite problematic. The aim of this paper is an estimation of the influence of invasive plants frequency on the explanation of their local abundance. We attempted to achieve it through: (1) assessment of occurrence of self-regenerating invasive plants in urban woodlands, (2) comparison of Random Forest modelling results for frequent and rare species. We hypothesized that the abundance of frequent species would be explained better than that of rare ones and that both rare and frequent species share a common hierarchy of the most important determinants. We found 15 taxa in almost two thirds of 1040 plots with a total number of 1068 occurrences. There were recorded 6 taxa of high frequency–<i>Prunus serotina</i>, <i>Quercus rubra</i>, <i>Acer negundo</i>, <i>Robinia pseudoacacia</i>, <i>Impatiens parviflora</i> and <i>Solidago</i> spp.–and 9 taxa of low frequency: <i>Acer saccharinum</i>, <i>Amelanchier spicata</i>, <i>Cornus</i> spp., <i>Fraxinus</i> spp., <i>Parthenocissus</i> spp., <i>Syringa vulgaris</i>, <i>Echinocystis lobata</i>, <i>Helianthus tuberosus</i>, <i>Reynoutria</i> spp. Random Forest’s models’ quality grows with the number of occurrences of frequent taxa but not of the rare ones. Both frequent and rare taxa share a similar hierarchy of predictors’ importance: Land use > Tree stand > Seed source and, for frequent taxa, Forest properties as well. We conclude that there is an ‘explanation jump’ at higher species frequencies, but rare species are surprisingly similar to frequent ones in their determinant’s hierarchy, with differences conforming with their respective stages of invasion.</p></div

The scheme of sampling plots location.

<p>SP = sampling plot, FS = forest subcompartment. SP1 is located near the outer border of the forest in the forest subcompartment FS1. SP2 and SP3 are located on both sides of a forest path, but in the same forest subcompartment FS2. SP4 and SP5 are located on both sides of the path, but in separate subcompartments FS2 and FS3.</p

Sum of importance of groups of predictors for frequent and rare species.

<p>Sum of importance of groups of predictors for frequent and rare species.</p

Model quality and the frequency of IAP species.

<p>Model quality and the frequency of IAP species.</p

Location of studied forests and SP included in analysis.

<p>In the background—the Global Monitoring for Environment and Security Urban Atlas dataset, licensed under the CC BY license [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168365#pone.0168365.ref041" target="_blank">41</a>].</p

The occurrence and abundance of frequent and rare IAP taxa in municipal urban woodlands.

<p>Calculated on the dataset of 1040 Sampling Plots (SP).</p

The dependence of predictors’ IncNodePurity on the frequency of species of concern, for different groups of predictors.

<p>The dependence of predictors’ IncNodePurity on the frequency of species of concern, for different groups of predictors.</p

The sum of RF importance for variable groups for frequent species.

<p>The numbers in circles are the subtotal of RF IncNodePurity importance based on the sum of squared residuals. The area of circles is proportional to the share of a given group in the sum of importance for the model of each species separately. Brown colour indicates woody and green indicates herbaceous species; N.A. = data not available.</p

The average importance of single predictors for frequent and rare species groups.

<p>The average importance of single predictors for frequent and rare species groups.</p

Quantitative studies on IAPs’ distribution.

<p>Quantitative studies on IAPs’ distribution.</p