Properties of Low-Cost WPCs Made from Alien Invasive Trees and rLDPE for Interior Use in Social Housing

Low-cost wood–plastic composites (WPCs) were developed from invasive trees and recycled low-density polyethylene. The aim was to produce affordable building materials for low-cost social housing in South Africa. Both raw materials are regarded as waste materials, and the subsequent product development adds value to the resources, while simultaneously reducing the waste stream. The production costs were minimised by utilising the entire biomass of Acacia saligna salvaged from clearing operations without any prior processing, and low-grade recycled low-density polyethylene to make WPCs without any additives. Different biomass/plastic ratios, particle sizes, and press settings were evaluated to determine the optimum processing parameters to obtain WPCs with adequate properties. The water absorption, dimensional stability, modulus of rupture, modulus of elasticity, tensile strength, and tensile moduli were improved at longer press times and higher temperatures for all blending ratios. This has been attributed to the crystallisation of the lignocellulose and thermally induced cross-linking in the polyethylene. An increased biomass ratio and particle size were positively correlated with water absorption and thickness swelling and inversely related with MOR, tensile strength, and density due to an incomplete encapsulation of the biomass by the plastic matrix. This study demonstrates the feasibility of utilising low-grade recycled polyethylene and the whole-tree biomass of A. saligna, without the need for pre-processing and the addition of expensive modifiers, to produce WPCs with properties that satisfy the minimum requirements for interior cladding or ceiling material.

How do invasive trees impact shrub layer diversity and productivity in temperate forests?

• Key message Invasive tree species alter taxonomic diversity and functioning of forest shrub layers: Prunus serotina increases shrub layer biomass two to three times but decreases its biodiversity, Robinia pseudoacacia slightly increases shrub layer biomass and has no effect on its biodiversity, while Quercus rubra both biomass and biodiversity of the shrub layer. • Context Although the impact of invasive trees on understory biodiversity is known, very little data exist about their influence on shrub layer biodiversity and productivity. • Aims To assess impacts of Prunus serotina Ehrh., Quercus rubra L., and Robinia pseudoacacia L. on shrub layer aboveground biomass, species composition, and alpha diversity. • Methods We measured stand structures in a set of 168 study plots established in Wielkopolski National Park (W Poland), and we compared biomass and diversity metrics using generalized mixed-effects linear models. • Results We found the lowest aboveground biomass of shrub layers in Q. rubra forests. P. sylvestris forests invaded by P. serotina had two to three times higher aboveground biomass than non-invaded forests. R. pseudoacacia forests had 27.8% higher shrub layer biomass than Quercus-Acer-Tilia forests. We found negative impacts of Q. rubra and negligible impacts of R. pseudoacacia on shrub layer alpha diversity metrics. However, the effect of Q. rubra was similar to native F. sylvatica. P. serotina negatively affected functional diversity, but its effects were lower in rich P. sylvestris forests than in poor P. sylvestris forests. • Conclusion The introduction of alien tree species alters ecosystem services and species diversity of shrub layers. The direction and magnitude of these alterations are alien species-specific and context-dependent. Therefore, their management should account for their impacts.

Impacts of invasive trees on alpha and beta diversity of temperate forest understories

Despite good recognition of distributions and spread mechanisms of the three most invasive trees in Europe (Prunus serotina, Quercus rubra and Robinia pseudoacacia), their impacts on forest biodiversity are unevenly recognized. Most studies cover only taxonomic alpha diversity, and only a single study included functional and phylogenetic diversity. Using a set of 186 study plots in western Poland we assessed the impacts of these invasive tree species on the alpha and beta taxonomic, functional and phylogenetic diversity of understory vascular plants. Alpha diversity was higher in R. pseudoacacia forests and lower in Q. rubra forests compared to mature native forests. Compared to non-invaded plantations and forests, alpha diversity was higher in P. sylvestris plantations invaded by P. serotina, but lower in invaded nutrient-poor P. sylvestris forests. Alien species richness was higher and beta diversity was lower in forests invaded by P. serotina or R. pseudoacacia than in non-invaded forests. In contrast, beta diversity was higher in Q. rubra forests than in native forests. We proved that invaded forests differed from non-invaded forests in species composition, but not always with decreased alpha and beta diversity. Impacts of particular invasive species also depended on the reference ecosystem properties (here mature native forests, which did not always have the highest biodiversity), which is a source of inconsistency in previous studies, usually referring to single native ecosystem types.

Early Detection of Invasive Exotic Trees Using UAV and Manned Aircraft Multispectral and LiDAR Data

Exotic conifers can provide significant ecosystem services, but in some environments, they have become invasive and threaten indigenous ecosystems. In New Zealand, this phenomenon is of considerable concern as the area occupied by invasive exotic trees is large and increasing rapidly. Remote sensing methods offer a potential means of identifying and monitoring land infested by these trees, enabling managers to efficiently allocate resources for their control. In this study, we sought to develop methods for remote detection of exotic invasive trees, namely Pinus sylvestris and P. ponderosa. Critically, the study aimed to detect these species prior to the onset of maturity and coning as this is important for preventing further spread. In the study environment in New Zealand’s South Island, these species reach maturity and begin bearing cones at a young age. As such, detection of these smaller individuals requires specialist methods and very high-resolution remote sensing data. We examined the efficacy of classifiers developed using two machine learning algorithms with multispectral and laser scanning data collected from two platforms—manned aircraft and unmanned aerial vehicles (UAV). The study focused on a localized conifer invasion originating from a multi-species pine shelter belt in a grassland environment. This environment provided a useful means of defining the detection thresholds of the methods and technologies employed. An extensive field dataset including over 17,000 trees (height range = 1 cm to 476 cm) was used as an independent validation dataset for the detection methods developed. We found that data from both platforms and using both logistic regression and random forests for classification provided highly accurate (kappa < 0.996 ) detection of invasive conifers. Our analysis showed that the data from both UAV and manned aircraft was useful for detecting trees down to 1 m in height and therefore shorter than 99.3% of the coning individuals in the study dataset. We also explored the relative contribution of both multispectral and airborne laser scanning (ALS) data in the detection of invasive trees through fitting classification models with different combinations of predictors and found that the most useful models included data from both sensors. However, the combination of ALS and multispectral data did not significantly improve classification accuracy. We believe that this was due to the simplistic vegetation and terrain structure in the study site that resulted in uncomplicated separability of invasive conifers from other vegetation. This study provides valuable new knowledge of the efficacy of detecting invasive conifers prior to the onset of coning using high-resolution data from UAV and manned aircraft. This will be an important tool in managing the spread of these important invasive plants.