Herein, we provide the ecological niches of gastrointestinal nematode infections in Guilan, Mazandaran, and Golestan provinces. For this purpose, 2688 fecal specimens of sheep and cattle were subjected to the flotation method. For modeling procedure, the results were analyzed by considering 23 bioclimatic and environmental variables as well as 96 points/locations. Maximum entropy (model MaxEnt) was used to visualize the spatial distribution of gastrointestinal nematodes. The relative importance of all variables was also assessed by using jackknife analysis. The highest proportion of sheep infection with strongyle-type egg was observed in Golestan province (57.8%) and the lowest in Guilan province (49.5%), and eggs per gram (EPG) was around 21–29. The parasites with the highest proportion of infection in both domestic animals included strongyle-type eggs. Among the different bioclimatic and environmental variables, the biggest contributor to habitat suitability of the gastrointestinal nematode presence was found to be minimum temperature of the coldest month (Bio6), precipitation of driest quarter (Bio17), precipitation of coldest quarter (Bio19), and altitude. The MaxEnt model was able to provide a suitable guidance for predicting the probability distribution of gastrointestinal nematodes under bioclimatic and environmental variables, and the findings pave way for integrated gastrointestinal nematode surveillance and control strategies in the southern strip of Caspian Sea. In addition, the low intensity of gastrointestinal nematodiasis in ruminants may be associated with the frequent administration of anthelmintic drugs, where actions are needed to investigate drug resistance in the areas concerned and to provide anthelmintic drugs administration in a targeted manner.

在此，我们提供了桂兰，马赞丹兰和哥列斯坦省的胃肠道线虫感染的生态位。为此，对2688只绵羊和牛的粪便标本进行了浮选法。对于建模程序，通过考虑23个生物气候和环境变量以及96个点/位置来分析结果。最大熵（模型MaxEnt）用于可视化胃肠道线虫的空间分布。还通过折刀分析法评估了所有变量的相对重要性。在Golestan省（57.8％）观察到羊被强壮型鸡蛋感染的比例最高（57.8％），而在Guilan省最低（49.5％），每克鸡蛋（EPG）约为21-29。在两只家畜中，感染率最高的寄生虫包括坚韧型卵。在不同的生物气候和环境变量中，发现胃肠道线虫存在的栖息地适宜性的最大贡献因素是最冷月份的最低温度（Bio6），最干燥季的沉淀（Bio17），最冷季的沉淀（Bio19）和高度。MaxEnt模型能够为预测生物气候和环境变量下胃肠道线虫的概率分布提供适当的指导，这一发现为里海南部地带的胃肠道线虫综合监测和控制策略铺平了道路。此外，