Eurasian beaver (Castor fiber) populations are expanding across Europe. Depending on location, beaver dams bring multiple benefits and/or require management. Using nationally available data, we developed: a Beaver Forage Index (BFI), identifying beaver foraging habitat, and a Beaver Dam Capacity (BDC) model, classifying suitability of river reaches for dam construction, to estimate location and number of dams at catchment scales. Models were executed across three catchments, in Great Britain (GB), containing beaver. An area of 6747 km² was analysed for BFI and 16,739 km of stream for BDC. Field surveys identified 258 km of channel containing beaver activity and 89 dams, providing data to test predictions. Models were evaluated using a categorical binomial Bayesian framework to calculate probability of foraging and dam construction. BFI and BDC models successfully categorised the use of reaches for foraging and damming, with higher scoring reaches being preferred. Highest scoring categories were ca. 31 and 79 times more likely to be used than the lowest for foraging and damming respectively. Zero-inflated negative binomial regression showed that modelled dam capacity was significantly related (p = 0.01) to observed damming and was used to predict numbers of dams that may occur. Estimated densities of dams, averaged across each catchment, ranged from 0.4 to 1.6 dams/km, though local densities may be up to 30 dams/km. These models provide fundamental information describing the distribution of beaver foraging habitat, where dams may be constructed and how many may occur. This supports the development of policy and management concerning the reintroduction and recolonisation of beaver.

中文翻译：

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建模欧亚海狸觅食栖息地和水坝适宜性，以预测英国整个流域水坝的位置和数量。

欧亚海狸（蓖麻纤维）种群正在欧洲各地扩展。根据位置的不同，海狸水坝会带来多种好处和/或需要管理。利用全国可获得的数据，我们开发了：海狸觅食指数（BFI），确定海狸觅食栖息地，以及海狸水坝容量（BDC）模型，对河段对水坝建设的适宜性进行分类，以估算集水规模的水坝位置和数量。 。在包括海狸在内的英国三个流域执行了模型。面积6747 km ²对BFI进行了分析，对BDC分析了16,739 km的流量。现场调查确定了258公里的海狸活动通道，其中包含海狸活动和89个水坝，为测试预测提供了数据。使用分类二项贝叶斯框架对模型进行评估，以计算觅食和大坝建设的可能性。BFI和BDC模型成功地将河段的觅食和筑坝用途分类，其中得分较高的河段是首选。得分最高的类别是ca。分别比最低的觅食和筑坝的可能性高31倍和79倍。零膨胀负二项式回归表明，建模大坝容量显着相关（p = 0.01）到观察到的水坝，并用来预测可能发生的水坝数量。每个流域的平均水坝密度估计范围为0.4至1.6个水坝/公里，尽管当地的密度可能高达30个水坝/公里。这些模型提供了描述海狸觅食栖息地分布的基本信息，可能在此处建造水坝，以及可能发生多少水坝。这支持了有关海狸重新引进和重新定殖的政策和管理的发展。