The presence of invasive plant species poses a substantial ecological impact,thus comprehensive evaluation of their potential range and risk under the influence of climate change is necessary.This study uses maximum e...The presence of invasive plant species poses a substantial ecological impact,thus comprehensive evaluation of their potential range and risk under the influence of climate change is necessary.This study uses maximum entropy(MaxEnt)modeling to forecast the likelihood of Leucaena leucocephala(Lam.)de Wit invasion in Saudi Arabia under present and future climate change scenarios.Utilizing the MaxEnt modeling,we integrated climatic and soil data to predict habitat suitability for the invasive species.We conducted a detailed analysis of the distribution patterns of the species,using climate variables and ecological factors.We focused on the important influence of temperature seasonality,temperature annual range,and precipitation seasonality.The distribution modeling used robust measures of area under the curve(AUC)and receiver-operator characteristic(ROC)curves,to map the invasion extent,which has a high level of accuracy in identifying appropriate habitats.The complex interaction that influenced the invasion of L.leucocephala was highlighted by the environmental parameters using Jackknife test.Presently,the actual geographic area where L.leucocephala was found in Saudi Arabia was considerably smaller than the theoretical maximum range,suggesting that it had the capacity to expand further.The MaxEnt model exhibited excellent prediction accuracy and produced reliable results based on the data from the ROC curve.Precipitation and temperature were the primary factors influencing the potential distribution of L.leucocephala.Currently,an estimated area of 216,342 km^(2)in Saudi Arabia was at a high probability of invasion by L.leucocephala.We investigated the potential for increased invasion hazards in the future due to climate change scenarios(Shared Socioeconomic Pathways(SSPs)245 and 585).The analysis of key climatic variables,including temperature seasonality and annual range,along with soil properties such as clay composition and nitrogen content,unveiled their substantial influence on the distribution dynamic of L.leucocephala.Our findings indicated a significant expansion of high risk zones.High-risk zones for L.leucocephala invasion in the current climate conditions had notable expansions projected under future climate scenarios,particularly evident in southern Makkah,Al Bahah,Madina,and Asir areas.The results,backed by thorough spatial studies,emphasize the need to reduce the possible ecological impacts of climate change on the spread of L.leucocephala.Moreover,the study provides valuable strategic insights for the management of invasion,highlighting the intricate relationship between climate change,habitat appropriateness,and the risks associated with invasive species.Proactive techniques are suggested to avoid and manage the spread of L.leucocephala,considering its high potential for future spread.This study enhances the overall comprehension of the dynamics of invasive species by combining modeling techniques with ecological knowledge.It also provides valuable information for decision-making to implement efficient conservation and management strategies in response to changing environmental conditions.展开更多
Distribution and enrichment of six elements (iron, zinc, copper, lead, cadmium and manganese) in surface bed sediments, collected from seventeen selected locations during pre-monsoon and postmonsoon periods, of the tr...Distribution and enrichment of six elements (iron, zinc, copper, lead, cadmium and manganese) in surface bed sediments, collected from seventeen selected locations during pre-monsoon and postmonsoon periods, of the tropical Chottanagpur plateau river Subarnarekha along with the ecological risks involved were investigated. Owing to the rich occurrence of mineral resources, the Subarnarekha river basin has a large scale presence of industrial and mining units especially in the Indian State of Jharkhand. An assessment, which involved examining distribution pattern of elements, comparative studies with sediment quality guidelines (SQGs) and geochemical background values and a sequential and integrated index analyses approach (containing contamination factor (CF), pollution load index (PLI), contamination degree (CD), enrichment factor (EF), geo-accumulation index (Igeo) and potential ecological risk index (PERI)), was followed to estimate enrichment and risks of elements in the bed sediments. Sediments collected from areas having abundance of population, industrial conglomerates and mining units recorded elevated element concentrations, which exceeded SQGs, and significantly higher values of CF, CD, PLI, EF, Igeo and PERI. Cadmium demonstrated surprising regularity in its enrichment;contributed most to the ecological risks;and high toxicity risks due to cadmium exceeded 64% of the sites. Moreover, chronic exposures of other elements would also lead to similar ecological risks. In addition to revealing potential ecological risks due to cadmium and other elements our investigation markedly highlighted anthropogenic control over sediment quality deterioration and some immediate sediment quality management strategies are needed to remediate and control river bed contamination.展开更多
This article adopts three soft computing techniques including support vector machine(SVM), least square support vector machine(LSSVM) and relevance vector machine(RVM) for prediction of status of epimetemorphic rock s...This article adopts three soft computing techniques including support vector machine(SVM), least square support vector machine(LSSVM) and relevance vector machine(RVM) for prediction of status of epimetemorphic rock slope. The input variables of SVM, LSSVM and RVM are bulk density, height, inclination, cohesion and internal friction angle. There are 53 datasets which have been used to develop the SVM, LSSVM and RVM models. The developed SVM, LSSVM and RVM give equations for prediction of status of epimetemorphic rock slope. The performance of SVM, LSSVM and RVM is 100%. A comparative study has been presented between the developed SVM, LSSVM and RVM. The results confirm that the developed SVM, LSSVM and RVM are effective tools for prediction of status of epimetemorphic rock slope.展开更多
基金the Researchers Supporting Project(RSP2024R347),King Saud University,Riyadh,Saudi Arabia.
文摘The presence of invasive plant species poses a substantial ecological impact,thus comprehensive evaluation of their potential range and risk under the influence of climate change is necessary.This study uses maximum entropy(MaxEnt)modeling to forecast the likelihood of Leucaena leucocephala(Lam.)de Wit invasion in Saudi Arabia under present and future climate change scenarios.Utilizing the MaxEnt modeling,we integrated climatic and soil data to predict habitat suitability for the invasive species.We conducted a detailed analysis of the distribution patterns of the species,using climate variables and ecological factors.We focused on the important influence of temperature seasonality,temperature annual range,and precipitation seasonality.The distribution modeling used robust measures of area under the curve(AUC)and receiver-operator characteristic(ROC)curves,to map the invasion extent,which has a high level of accuracy in identifying appropriate habitats.The complex interaction that influenced the invasion of L.leucocephala was highlighted by the environmental parameters using Jackknife test.Presently,the actual geographic area where L.leucocephala was found in Saudi Arabia was considerably smaller than the theoretical maximum range,suggesting that it had the capacity to expand further.The MaxEnt model exhibited excellent prediction accuracy and produced reliable results based on the data from the ROC curve.Precipitation and temperature were the primary factors influencing the potential distribution of L.leucocephala.Currently,an estimated area of 216,342 km^(2)in Saudi Arabia was at a high probability of invasion by L.leucocephala.We investigated the potential for increased invasion hazards in the future due to climate change scenarios(Shared Socioeconomic Pathways(SSPs)245 and 585).The analysis of key climatic variables,including temperature seasonality and annual range,along with soil properties such as clay composition and nitrogen content,unveiled their substantial influence on the distribution dynamic of L.leucocephala.Our findings indicated a significant expansion of high risk zones.High-risk zones for L.leucocephala invasion in the current climate conditions had notable expansions projected under future climate scenarios,particularly evident in southern Makkah,Al Bahah,Madina,and Asir areas.The results,backed by thorough spatial studies,emphasize the need to reduce the possible ecological impacts of climate change on the spread of L.leucocephala.Moreover,the study provides valuable strategic insights for the management of invasion,highlighting the intricate relationship between climate change,habitat appropriateness,and the risks associated with invasive species.Proactive techniques are suggested to avoid and manage the spread of L.leucocephala,considering its high potential for future spread.This study enhances the overall comprehension of the dynamics of invasive species by combining modeling techniques with ecological knowledge.It also provides valuable information for decision-making to implement efficient conservation and management strategies in response to changing environmental conditions.
文摘Distribution and enrichment of six elements (iron, zinc, copper, lead, cadmium and manganese) in surface bed sediments, collected from seventeen selected locations during pre-monsoon and postmonsoon periods, of the tropical Chottanagpur plateau river Subarnarekha along with the ecological risks involved were investigated. Owing to the rich occurrence of mineral resources, the Subarnarekha river basin has a large scale presence of industrial and mining units especially in the Indian State of Jharkhand. An assessment, which involved examining distribution pattern of elements, comparative studies with sediment quality guidelines (SQGs) and geochemical background values and a sequential and integrated index analyses approach (containing contamination factor (CF), pollution load index (PLI), contamination degree (CD), enrichment factor (EF), geo-accumulation index (Igeo) and potential ecological risk index (PERI)), was followed to estimate enrichment and risks of elements in the bed sediments. Sediments collected from areas having abundance of population, industrial conglomerates and mining units recorded elevated element concentrations, which exceeded SQGs, and significantly higher values of CF, CD, PLI, EF, Igeo and PERI. Cadmium demonstrated surprising regularity in its enrichment;contributed most to the ecological risks;and high toxicity risks due to cadmium exceeded 64% of the sites. Moreover, chronic exposures of other elements would also lead to similar ecological risks. In addition to revealing potential ecological risks due to cadmium and other elements our investigation markedly highlighted anthropogenic control over sediment quality deterioration and some immediate sediment quality management strategies are needed to remediate and control river bed contamination.
文摘This article adopts three soft computing techniques including support vector machine(SVM), least square support vector machine(LSSVM) and relevance vector machine(RVM) for prediction of status of epimetemorphic rock slope. The input variables of SVM, LSSVM and RVM are bulk density, height, inclination, cohesion and internal friction angle. There are 53 datasets which have been used to develop the SVM, LSSVM and RVM models. The developed SVM, LSSVM and RVM give equations for prediction of status of epimetemorphic rock slope. The performance of SVM, LSSVM and RVM is 100%. A comparative study has been presented between the developed SVM, LSSVM and RVM. The results confirm that the developed SVM, LSSVM and RVM are effective tools for prediction of status of epimetemorphic rock slope.
