Heavy metal pollution in soils caused by mining has led to major environmental problems around the globe and seriously threatens the ecological environment. The assessment of heavy metal pollution and the local phytoremediation potential of contaminated sites is an important prerequisite for phytoremediation. Therefore, the purpose of this study was to understand the characteristics of heavy metal pollution around a copper-nickel mine tailings pond and screen local plant species that could be potentially suitable for phytoremediation. The results showed that Cd, Cu, Ni, and Cr in the soil around the tailings pond were at the heavy pollution level, Mn and Pb pollution was moderate, and Zn and As pollution was light; The positive matrix factorization (PMF) model results showed that the contributions made by industrial pollution to Cu and Ni were 62.5% and 66.5%, respectively, atmospheric sedimentation and agricultural pollution contributions to Cr and Cd were 44.6% and 42.8%, respectively, the traffic pollution contribution to Pb was 41.2%, and the contributions made by natural pollution sources to Mn, Zn, and As were 54.5%, 47.9%, and 40.0% respectively. The maximum accumulation values for Cu, Ni, Cr, Cd, and As in 10 plants were 53.77, 102.67, 91.10, 1.16 and 7.23 mg/kg, respectively, which exceeded the normal content of heavy metals in plants.Ammophila breviligulataFernald had the highest comprehensive extraction coefficient (CEI) and comprehensive stability coefficient (CSI) at 0.81 and 0.83, respectively. These results indicate that the heavy metal pollution in the soil around the copper nickel mine tailings pond investigated in this study is serious and may affect the normal growth of plants.Ammophila breviligulataFernald has a strong comprehensive remediation capacity and can be used as a remediation plant species for multiple metal compound pollution sites.

As decision-making tools helping to improve the understanding of soil quality, soil quality assessment and heavy metal pollution assessment are very important for the remediation of heavy metal soil pollution. In the past, soil quality and heavy metal pollution have been studied separately, and few studies have combined them. The desert steppe in the Northwest Arid Region is an important pasture resource in China, and its soil safety has always been the focus of attention. Therefore, to understand the impact of tailing stockpiles on the soil quality of desert steppe, this study analyzed 18 indicators in the sample and analyzed the soil quality status of desert steppe based on the soil quality index (SQI) and Nemerow pollution index (P_com). The main conclusions are as follows. (1) The evaluation results of heavy metal soil pollution show that the heavy metals Cu, Ni, Cr and Cd are significant polluters, Mn is a moderate polluter and Zn is a slight polluter. The results of the positive matrix factorization model show that Cu and Ni come from industrial sources; Cr, Cd and Zn come from industrial and traffic sources; and Mn comes from natural sources. (2) Regarding the study area, the generated minimum data set contains clay, pH, soil organic matter, available phosphorus, urease and neutral phosphatase. (3) The results of the SQI show that the soil in the study area is grade V (SQI-TDS_ave (total data set) = 0.42; SQI-MDS_ave (minimum data set) = 0.39), and the soil condition is very poor. 4) The linear fitting results show that the SQI-MDS was positively correlated with the SQI-TDS (R² = 0.79), and SQI-MDS and SQI-TDS were negatively correlated with the P_com (R² > 0.6). Therefore, the leakage of acid mine drainage from tailings pond accumulation has led to a significant decline in the soil quality of this desert steppe, and effective ecological restoration measures are urgently needed to ensure the sustainable stability of the steppe ecosystem.

The gum acacia Senegalia senegal (L.) Britton (Fabales: Fabaceae) is a drought-tolerant plant belonging to the genus Acacia of the Leguminosae family, possessing significant economic and ecological value. Despite its importance, there is a knowledge gap regarding the potential impact of climate change on the distribution of S. senegal, crucial for the conservation of plant resources and optimizing its use in introductory silviculture. In this study, we selected 23 environmental variables and utilized the optimized maximum entropy (MaxEnt) model to analyze the key environmental factors affecting the distribution of S. senegal worldwide and simulate the current and future distribution range of S. senegal in Pakistan under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 climate change scenarios. The results highlight key environmental factors influencing the distribution of S. senegal, including BIO3 (isothermally), BIO4 (coefficient of seasonal variation of temperature), BIO11 (mean temperature of the coldest season), and BIO12 (annual precipitation). Regions with higher and less fluctuating temperatures exhibit a higher potential for S. senegal distribution. Currently, suitable habitats of S. senegal are concentrated in the southern region of Pakistan, covering provinces such as Punjab, Sindh, and Balochistan, with highly suitable habitats accounting for 6.06% of the total area. Under the current climatic conditions, this study identifies the spatial patterns of suitable habitats and their concentration in specific regions. With climate change, a notable expansion of suitable habitats towards higher latitudes is observed, with the most significant expansion under the extremely severe climate change scenario (SSP5-8.5), reaching 223.45% of the current level. The results of this study enhance our understanding of the dynamics of S. senegal distribution under climate change and offer valuable insights into the long-term introduction of S. senegal for afforestation and soil conservation in Pakistan. This study provides theoretical support for the sustainable development of the local ecosystem and socio-economy, emphasizing the importance of proactive measures to adapt to changing climatic conditions.