Ratcliff Felix, Bartolome James, Macaulay Luke, Spiegal Sheri, White Michael D
Department of Environmental Science Policy and Management University of California, Berkeley Berkeley California.
USDA-ARS-Jornada Experimental Range Las Cruces New Mexico.
Ecol Evol. 2018 Apr 19;8(10):4907-4918. doi: 10.1002/ece3.4057. eCollection 2018 May.
Ecological sites and state-and-transition models are useful tools for generating and testing hypotheses about drivers of vegetation composition in rangeland systems. These models have been widely implemented in upland rangelands, but comparatively, little attention has been given to developing ecological site concepts for rangeland riparian areas, and additional environmental criteria may be necessary to classify riparian ecological sites. Between 2013 and 2016, fifteen study reaches on five creeks were studied at Tejon Ranch in southern California. Data were collected to describe the relationship between riparian vegetation composition, environmental variables, and livestock management; and to explore the utility of ecological sites and state-and-transition models for describing riparian vegetation communities and for creating hypotheses about drivers of vegetation change. Hierarchical cluster analysis was used to classify the environmental and vegetation data (15 stream reaches × 4 years) into two ecological sites and eight community phases that comprised three vegetation states. Classification and regression tree (CART) analysis was used to determine the influence of abiotic site variables, annual precipitation, and cattle activity on vegetation clusters. Channel slope explained the greatest amount of variation in vegetation clusters; however, soil texture, geology, watershed size, and elevation were also selected as important predictors of vegetation composition. The classification tree built with this limited set of abiotic predictor variables explained 90% of the observed vegetation clusters. Cattle grazing and annual precipitation were not linked to qualitative differences in vegetation. Abiotic variables explained almost all of the observed riparian vegetation dynamics-and the divisions in the CART analysis corresponded roughly to the ecological sites-suggesting that ecological sites are well-suited for understanding and predicting change in this highly variable system. These findings support continued development of riparian ecological site concepts and state-and-transition models to aid decision making for conservation and management of rangeland riparian areas.
生态位和状态-转换模型是用于生成和检验有关牧场系统植被组成驱动因素假设的有用工具。这些模型已在山地牧场广泛应用，但相比之下，针对牧场河岸地区生态位概念的开发关注较少，可能需要额外的环境标准来对河岸生态位进行分类。2013年至2016年期间，在南加州的蒂洪牧场对五条溪流的15个研究河段进行了研究。收集数据以描述河岸植被组成、环境变量和牲畜管理之间的关系；并探索生态位和状态-转换模型在描述河岸植被群落以及创建植被变化驱动因素假设方面的效用。层次聚类分析用于将环境和植被数据（15个河段×4年）分类为两个生态位和八个群落阶段，这些阶段包括三种植被状态。分类与回归树（CART）分析用于确定非生物位变量、年降水量和牛群活动对植被聚类的影响。河道坡度解释了植被聚类中最大的变化量；然而，土壤质地、地质、流域面积和海拔也被选为植被组成的重要预测因子。用这组有限的非生物预测变量构建的分类树解释了90%的观测植被聚类。牛群放牧和年降水量与植被的定性差异无关。非生物变量几乎解释了所有观测到的河岸植被动态——CART分析中的划分大致对应于生态位——这表明生态位非常适合理解和预测这个高度可变系统中的变化。这些发现支持继续发展河岸生态位概念和状态-转换模型，以协助牧场河岸地区保护和管理的决策制定。
