Department of Fisheries & Wildlife, Oregon State University, 104 Nash Hall, Corvallis, OR, 97331, USA.
Department of Statistics, Oregon State University, Corvallis, OR, 97331, USA.
Environ Monit Assess. 2019 Jun 20;191(Suppl 1):296. doi: 10.1007/s10661-019-7323-5.
We analyzed data from 1138 wetland sites across the conterminous United States (US) as part of the 2011 National Wetland Condition Assessment (NWCA) to investigate the response of indicators of wetland quality to indicators of human disturbance at regional and continental scales. The strength and nature of these relationships in wetlands have rarely been examined over large regions, due to the paucity of large-scale datasets. Wetland response indicators were a multimetric index of vegetation condition (VMMI), percent relative cover of alien plant species, soil lead and phosphorus, and water column total nitrogen and total phosphorus. Site-level disturbance indices were generated from field observations of disturbance types within a circular 140-m radius area around the sample point. Summary indices were calculated representing disturbances for ditching, damming, filling/erosion, hardening, vegetation replacement, and vegetation removal. Landscape-level disturbance associated with agricultural and urban land cover, roads, and human population were based on GIS data layers quantified in 200, 500, and 1000-m circular buffers around each sample point. Among these three buffer sizes, the landscape disturbance indicators were highly correlated and had similar relationships with the response indictors. Consequently, only the 1000-m buffer data were used for subsequent analyses. Disturbance-response models built using only landscape- or only site-level disturbance variables generally explained a small portion of the variance in the response variables (R < 0.2), whereas models using both types of disturbance data were better at predicting wetland responses. The VMMI was the response variable with the strongest relationship to the disturbances assessed in the NWCA (national model R = 0.251). National multiple regression models for the soil and water chemistry and percent alien cover responses to disturbance indices were not significant. The generally low percentage of significant models and the wide variation in predictor variables suggests that stressor-response relationships vary considerably across the diversity of wetland types and landscape settings found across the conterminous US. Logistic regression modeling was more informative, resulting in significant national and regional models predicting site presence/absence of alien species and/or the concentration of lead in wetland soils above background.
我们分析了美国本土 1138 个湿地地点的数据,这些数据来自 2011 年的国家湿地状况评估(NWCA),旨在研究在区域和大陆尺度上,湿地质量指标对人类干扰指标的响应。由于缺乏大规模数据集,这些关系在湿地中的强度和性质很少在大区域内进行研究。湿地响应指标是植被状况的多指标指数(VMMI)、外来植物物种的相对盖度百分比、土壤中的铅和磷以及水柱中的总氮和总磷。基于样本点周围 140 米半径内的干扰类型的实地观测,生成了站点级别的干扰指数。摘要指数代表了沟渠、堤坝、填/蚀、硬化、植被替换和植被清除等干扰类型。与农业和城市土地覆盖、道路和人口相关的景观级别的干扰是基于 GIS 数据层在每个样本点周围的 200、500 和 1000 米的圆形缓冲区中量化的。在这三种缓冲区大小中,景观干扰指标高度相关,与响应指标具有相似的关系。因此,仅使用 1000 米缓冲区数据进行后续分析。仅使用景观或仅使用站点级别的干扰变量构建的干扰-响应模型通常只能解释响应变量的一小部分方差(R < 0.2),而使用两种类型的干扰数据的模型则更能预测湿地的响应。VMMI 是与 NWCA(国家模型 R = 0.251)评估的干扰关系最强的响应变量。用于土壤和水化学以及对干扰指数的外来物种覆盖百分比的国家多元回归模型不显著。显著模型的百分比通常较低,预测变量的变化范围较大,这表明胁迫-响应关系在整个美国本土的各种湿地类型和景观环境中存在很大差异。逻辑回归建模更具信息量,导致国家和区域模型显著,可预测外来物种在特定地点的存在/不存在以及湿地土壤中铅浓度高于背景值。