The bioaccumulation and rhizofiltration potential of P. stratiotes for heavy metals were investigated to mitigate water pollution in the Egyptian wetlands. Plant and water samples were collected monthly through nine quadrats equally distributed along three sites at Al-Sero drain in Giza Province. The annual mean of the shoot biomass was 10 times that of the root. The concentrations of shoot heavy metals fell in the order: Fe < Mn < Cr < Pb < Cu < Zn < Ni < Co < Cd, while that of the roots were: Fe < Mn < Cr < Pb < Zn < Ni < Co < Cu < Cd. The bio-concentration factor (BCF) of most investigated heavy metals, except Cr and Pb, was greater than 1000, while the translocation factor (TF) of most investigated metals, except Pb and Cu, did not exceed one. The rhizofiltration potential (RP) of heavy metals was higher than 1000 for Fe, and 100 for Cr, Pb and Cu. Significant positive correlations between Fe and Cu in water with those in plant roots and leaves, respectively were recorded, which, in addition to the high BCF and RP, indicate the potential use of P. stratiotes in mitigating these toxic metals.

Aim: As a prominent geographical distribution centre for the dark coniferous forests, mountains of Southwest China (MSWC) is experiencing an unprecedented warming trend, posing severe challenges to the survival of dominant fir (Abies) species. Although plant's migration ability is a prerequisite for its survival in changing environments, it has often been ignored in species distribution models (SDMs). This study aimed to quantify the magnitude and direction of range changes by the year 2080 for six dominant fir species, that isAbies recurvata,Abies faxoniana,Abies squamata,Abies ernestii,Abies forrestiiandAbies georgei, with an emphasis on exploring the relationship between migration ability and projected distributions.Location: The mountains of Southwest China.Methods: We applied the Maximum Entropy (Maxent) algorithm to calibrate ecological niche models and to project the climatically suitable areas (CSAs) of each species under two emission scenarios (RCP 4.5 and RCP 8.5). Additionally, we delimited future species ranges by three migration scenarios (full‐, no‐ and partial‐migration scenarios).Results: The simulations showed the distinctive responses of the six fir species to anthropogenic climate change (ACC). By 2080, the distribution areas ofAbies recurvatawere projected to decline only in the no‐migration scenario but increase under the full‐ and partial‐migration scenarios, while the other five species were projected to decline in the majority of emission × migration scenarios. Fir species in the southern region were predicted to be more vulnerable to ACC due to the larger losses in CSAs and a stronger effect of the partial‐migration scenario on the newly colonized areas of this group. The studied species showed a simulated migration trend (northward and westward) to the interior Qinghai‐Tibet Plateau under ACC.Main conclusions: Benefits or losses for species under ACC depended on the geographical location, their ecological niches and migration abilities, which provide essential insights for a spatial conservation assessment of biodiversity hotspots in the future.

Prosopis juliflora is one of the most problematic invasive trees in tropical and subtropical regions. Understanding driving forces affecting the potential global distribution would help in managing its current and future spread. The role of climate on the global spatial distribution of P. juliflora has been well studied, but little is known about the role of soil and human impacts as potential drivers. Here, we used maximum entropy (MaxEnt) for species distribution modelling to understand the role of climate (C), soil (S) and human impacts (H), C+S, and C+S+H in controlling the potential invasion range of P. juliflora, and to project its global potential invasive risk. We defined the top threatened global biomes, as predicted by the best-selected model. The incorporation of the edaphic factors improved the model performance and enhanced the accuracy of the outcome. Our findings revealed that the potential invasion risk increases with increases in mean temperature of the driest quarter (Bio9), soil alkalinity and clay fractions. Arid and semi-arid lands are at the highest risk of invasion than other moist biomes.