Anticipating the potential distribution of Fasciola spp. in Gilan province of Iran: Insights from MaxEnt and climate change scenarios

IF 1.6 3区 农林科学 Q2 AGRICULTURE, DAIRY & ANIMAL SCIENCE
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Abstract

Fasciolosis, a parasitic disease affecting humans and animals, is uniquely influenced by climatic and environmental factors. Gilan province in northern Iran is recognized as a high-endemic area for this parasite. This study aims to assess the prevalence of fasciolosis in Gilan province during the current period and forecast the distribution pattern of the parasite in future periods by analyzing climatic variables and identifying the most critical factors impacting Fasciola. To evaluate the present status of fasciolosis in Gilan, we collected 189 sheep fecal samples from different parts of the province and quantified eggs per gram of feces in each sample. Meteorological and environmental data were obtained and clipped to the study area. A total of 19 presence points were used to model the habitat suitability of Fasciola spp. through the maximum entropy (MaxEnt) algorithm, with jackknife analysis to determine variable importance. To project the potential distribution of Fasciola spp. in Gilan province under future scenarios, we employed MaxEnt using current (1970–2000) and projected climatic data based on three representative concentration pathway scenarios (RCP 2.6, RCP 4.5, and RCP 8.5) to predict habitat suitability in 2030, 2050, and 2070.
The results of this study indicate the proportion of Fasciola spp. infection was highest in Talesh (46.37 %) and Langarud (45.7 %), while Rudsar (0 %) and Shaft (16.25 %) exhibited the lowest infection rates in Gilan province. MaxEnt modeling highlighted the significance of bioclimatic variables, particularly those associated with vegetation and temperature, such as temperature seasonality (Bio4) and normalized difference vegetation index (NDVI). The ecological niche modeling illustrated that the highest potential distribution for Fasciola in Gilan province is concentrated in the north-western and central regions, exhibiting an 80–100 % potential. However, projections for the future indicate a decrease to less than 20 % suitability for most of the province under all three scenarios until 2070. This study provides valuable insights into the dynamic relationship between climatic variables and Fasciola distribution, enabling better preparedness and control strategies for this trematode in Gilan province and other regions with similar climates.
预测伊朗吉兰省法氏囊病菌的潜在分布:从 MaxEnt 和气候变化情景中获得的启示
法氏囊病是一种影响人类和动物的寄生虫病,受到气候和环境因素的独特影响。伊朗北部的吉兰省被认为是这种寄生虫的高端流行区。本研究旨在评估吉兰省当前的法氏囊病流行情况,并通过分析气候变量和确定影响法氏囊病的最关键因素,预测寄生虫在未来时期的分布模式。为了评估吉兰省法氏囊病的现状,我们从该省不同地区收集了 189 份绵羊粪便样本,并对每份样本中每克粪便的虫卵进行了量化。我们还获得了气象和环境数据,并将其剪切到研究区域。共使用了 19 个存在点,通过最大熵(MaxEnt)算法建立了法氏囊属动物栖息地适宜性模型,并使用杰克刀分析法确定变量的重要性。为了预测吉兰省在未来情况下的潜在法氏囊属分布,我们采用 MaxEnt 算法,使用当前(1970-2000 年)和基于三种代表性浓度路径情景(RCP 2.6、RCP 4.5 和 RCP 8.5)的预测气候数据来预测吉兰省的生境适宜性。研究结果表明,在吉兰省,Talesh(46.37%)和Langarud(45.7%)的法氏囊属感染率最高,而Rudsar(0%)和Shaft(16.25%)的感染率最低。MaxEnt 模型突出了生物气候变量的重要性,尤其是与植被和温度相关的变量,如温度季节性(Bio4)和归一化植被指数(NDVI)。生态位建模表明,吉兰省法氏囊虫的最高分布潜力集中在西北部和中部地区,潜力为 80%-100%。然而,对未来的预测表明,在所有三种情况下,直到 2070 年,该省大部分地区的适宜性都将下降到 20% 以下。这项研究为了解气候变量与法氏囊分布之间的动态关系提供了宝贵的见解,有助于吉兰省和其他气候相似的地区更好地防范和控制法氏囊虫。
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来源期刊
Small Ruminant Research
Small Ruminant Research 农林科学-奶制品与动物科学
CiteScore
3.10
自引率
11.10%
发文量
210
审稿时长
12.5 weeks
期刊介绍: Small Ruminant Research publishes original, basic and applied research articles, technical notes, and review articles on research relating to goats, sheep, deer, the New World camelids llama, alpaca, vicuna and guanaco, and the Old World camels. Topics covered include nutrition, physiology, anatomy, genetics, microbiology, ethology, product technology, socio-economics, management, sustainability and environment, veterinary medicine and husbandry engineering.
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