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首页|Predicting potential invasion risks of Leucaena leucocephala (Lam.) de Wit in the arid area of Saudi Arabia

Predicting potential invasion risks of Leucaena leucocephala (Lam.) de Wit in the arid area of Saudi Arabia

Haq S MARIFATUL

Predicting potential invasion risks of Leucaena leucocephala (Lam.) de Wit in the arid area of Saudi Arabia

Predicting potential invasion risks of Leucaena leucocephala (Lam.) de Wit in the arid area of Saudi Arabia

Haq S MARIFATUL

作者信息

摘要

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 km2 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.

Abstract

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 km2 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.

关键词

area under the curve/invasive species/invasion risks/climate change/MaxEnt model

引用本文复制引用

Haq S MARIFATUL.Predicting potential invasion risks of Leucaena leucocephala (Lam.) de Wit in the arid area of Saudi Arabia[EB/OL].(2024-07-31)[2025-12-13].https://chinaxiv.org/abs/202407.00363.

学科分类

环境科学技术现状/环境生物学/植物学

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