Dataset Information

Simple yet effective: Historical proximity variables improve the species distribution models for invasive giant hogweed (Heracleum mantegazzianum s.l.) in Poland.

ABSTRACT: Species distribution models are scarcely applicable to invasive species because of their breaking of the models' assumptions. So far, few mechanistic, semi-mechanistic or statistical solutions like dispersal constraints or propagule limitation have been applied. We evaluated a novel quasi-semi-mechanistic approach for regional scale models, using historical proximity variables (HPV) representing a state of the population in a given moment in the past. Our aim was to test the effects of addition of HPV sets of different minimal recentness, information capacity and the total number of variables on the quality of the species distribution model for Heracleum mantegazzianum on 116000 km2 in Poland. As environmental predictors, we used fragments of 103 1×1 km, world- wide, free-access rasters from WorldGrids.org. Single and ensemble models were computed using BIOMOD2 package 3.1.47 working in R environment 3.1.0. The addition of HPV improved the quality of single and ensemble models from poor to good and excellent. The quality was the highest for the variants with HPVs based on the distance from the most recent past occurrences. It was mostly affected by the algorithm type, but all HPV traits (minimal recentness, information capacity, model type or the number of the time periods) were significantly important determinants. The addition of HPVs improved the quality of current projections, raising the occurrence probability in regions where the species had occurred before. We conclude that HPV addition enables semi-realistic estimation of the rate of spread and can be applied to the short-term forecasting of invasive or declining species, which also break equal-dispersal probability assumptions.

SUBMITTER: Medrzycki P

PROVIDER: S-EPMC5604976 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The impact of invasion on diversity varies widely and remains elusive. Despite the considerable attempts to understand mechanisms of biological invasion, it is largely unknown whether some communities' characteristics promote biological invasion, or whether some inherent characteristics of invaders enable them to invade other communities. Our aims were to assess the impact of one of the massive plant invaders of Scandinavia on vascular plant species diversity, disentangle attributes of invasible and noninvasible communities, and evaluate the relationship between invasibility and genetic diversity of a dominant invader. We studied 56 pairs of Heracleum persicum Desf. ex Fisch.-invaded and noninvaded plots from 12 locations in northern Norway. There was lower native cover, evenness, taxonomic diversity, native biomass, and species richness in the invaded plots than in the noninvaded plots. The invaded plots had nearly two native species fewer than the noninvaded plots on average. Within the invaded plots, cover of H. persicum had a strong negative effect on the native cover, evenness, and native biomass, and a positive association with the height of the native plants. Plant communities containing only native species appeared more invasible than those that included exotic species, particularly H. persicum. Genetic diversity of H. persicum was positively correlated with invasibility but not with community diversity. The invasion of a plant community by H. persicum exerts consistent negative pressure on vascular plant diversity. The lack of positive correlation between impacts and genetic diversity of H. persicum indicates that even a small founder population may cause high impact. We highlight community stability or saturation as an important determinant of invasibility. While the invasion by H. persicum may decrease susceptibility of a plant community to further invasion, it severely reduces the abundance of native species and makes them more vulnerable to competitive exclusion.

Dataset Information

Simple yet effective: Historical proximity variables improve the species distribution models for invasive giant hogweed (Heracleum mantegazzianum s.l.) in Poland.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets