The unabating rise in the number of species introduced outside of their native range makes predicting the spread of alien species an urgent challenge. Most predictions use models of the ecological niche of a species to identify suitable areas for invasion, but these predictions may have limited accuracy. Here, using the global alien avifauna, we demonstrate an alternative approach for predicting alien spread based on the environmental resistance of the landscape. This approach does not require any information on the ecological niche of the invading species and, instead, uses gradients of biotic similarity among native communities in the invaded region to predict the most likely routes of spread. We show that environmental resistance predicts patterns of spread better than a null model of random dispersal or a model based on climate matching to the native range of each species. Applying this approach to simulate future spread reveals major regional differences in projected invasion risk, shaped by proximity to existing invasion hotspots as well as gradients in environmental resistance. Our results show how environmental resistance may provide a general and complementary approach for predicting invasion risk that can be rapidly deployed even when information on the niche or the identity of potential invaders is unknown.

在其原生范围之外引入的物种数量不断增加，这使得预测外来物种的传播成为一项紧迫的挑战。大多数预测使用物种生态位模型来确定适合入侵的区域，但这些预测的准确性可能有限。在这里，我们使用全球外星鸟类，展示了一种基于景观环境阻力预测外星人传播的替代方法。这种方法不需要有关入侵物种生态位的任何信息，而是使用入侵地区本地社区之间的生物相似性梯度来预测最可能的传播途径。我们表明，环境抗性比随机扩散的零模型或基于与每个物种的原生范围匹配的气候模型更好地预测传播模式。应用这种方法来模拟未来的传播揭示了预计入侵风险的主要区域差异，这些差异是由接近现有入侵热点以及环境阻力梯度决定的。我们的研究结果表明，即使在有关生态位或潜在入侵者身份的信息未知的情况下，环境抗性如何为预测入侵风险提供一种通用且互补的方法，该方法可以快速部署。与现有入侵热点的接近程度以及环境抵抗力的梯度有关。我们的研究结果表明，即使在有关生态位或潜在入侵者身份的信息未知的情况下，环境抗性如何为预测入侵风险提供一种通用且互补的方法，该方法可以快速部署。与现有入侵热点的接近程度以及环境抵抗力的梯度有关。我们的研究结果表明，即使在有关生态位或潜在入侵者身份的信息未知的情况下，环境抗性如何为预测入侵风险提供一种通用且互补的方法，该方法可以快速部署。