State-and-transition models (STMs) are tools used in rangeland management to describe linear and nonlinear vegetation dynamics as conceptual models. STMs can be improved by including additional ecosystem services, such as wildlife habitat, so that managers can predict how local populations might respond to state changes and to illustrate the tradeoffs in managing for different ecosystem services. Our objective was to incorporate songbird density into an STM developed for sagebrush rangelands in northwest Colorado to guide local management of sagebrush birds. The STM included two shrub-dominated community phases, a native grassland state, and a shrubland and grassland phase within an exotic-dominated state. We surveyed plots for songbirds, collected a suite of vegetation indicators at each plot, and quantified songbird habitat relationships with count-based regression models. We then used the estimated models to predict songbird density based on average vegetation conditions per state or community phase. Moderate or increasing shrub cover were important predictors for shrubland-associated species, and responses to understory components varied by species. In the STM, we predicted higher densities of shrubland-associated bird species in the shrub-dominated phases and higher densities of grassland-associated bird species in the state and phase lacking shrub cover. No single state or phase captured the highest density for all songbirds, illustrating the value of alternative states. Our results also demonstrate the utility of displaying traditional wildlife count models against the range of vegetation conditions associated with each state or phase to understand how wildlife density can vary within states and phases. Our approach can assist land managers to gauge the potential impacts of land-use decisions and natural vegetation variability on wildlife, especially for species of conservation concern.

状态和转换模型 (STM) 是牧场管理中使用的工具，用于将线性和非线性植被动态描述为概念模型。STM 可以通过包括额外的生态系统服务（例如野生动物栖息地）来改进，以便管理人员可以预测当地人口可能如何应对状态变化，并说明管理不同生态系统服务的权衡。我们的目标是将鸣禽密度纳入为科罗拉多西北部山艾树牧场开发的 STM 中，以指导当地对山艾树鸟类的管理。STM 包括两个以灌木为主的群落阶段，一个原生草原状态，以及一个外来主导状态内的灌木和草地阶段。我们调查了鸣禽的地块，在每个地块收集了一套植被指标，并使用基于计数的回归模型量化鸣禽栖息地关系。然后，我们使用估计模型根据每个州或社区阶段的平均植被条件来预测鸣禽密度。中等或增加的灌木覆盖是灌木相关物种的重要预测因子，对林下成分的反应因物种而异。在 STM 中，我们预测在灌木主导阶段与灌木地相关的鸟类物种密度较高，而在缺乏灌木覆盖的州和阶段与草地相关的鸟类物种密度较高。对于所有鸣禽，没有单一状态或阶段获得最高密度，这说明了替代状态的价值。我们的结果还证明了针对与每个州或阶段相关的植被条件范围显示传统野生动物计数模型的效用，以了解野生动物密度如何在州和阶段内变化。我们的方法可以帮助土地管理者衡量土地使用决策和自然植被变异对野生动物的潜在影响，尤其是对保护关注的物种。