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Characterizing nonnative plants in wetlands across the conterminous United States

机译:在孔雀石湿地中表征非湿地植物

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Nonnative plants are widely recognized as stressors to wetlands and other ecosystems. They may compete with native plant species or communities and alter ecosystem properties, which can affect ecological condition, posing challenges to resource managers. As part of the United States Environmental Protection Agency's National Wetland Condition Assessment (NWCA), we characterized the status of nonnative plants in wetlands across the conterminous United States (US). Our primary goals were to (1) document the composition of nonnative taxa at 1138 NWCA sites sampled in 2011 and (2) estimate the areal extent of wetland under stress from nonnative plants within the NWCA 2011 sampled population of similar to 25 million ha of wetland (represented by 967 sampled probability sites and the NWCA survey design). A total of 443 unique nonnative taxa were observed, encompassing a species pool adapted to diverse ecological conditions. For individual sites, the number of nonnative taxa ranged from 0 to 29, and total absolute cover of nonnatives ranged from 0 to 160%. We devised the nonnative plant indicator (NNPI) as a categorical indicator of stress (low to very high) from the collective set of nonnative plant taxa occurring at a particular location, based on a decision matrix of exceedance values for nonnative richness, relative frequency, and relative cover. Wetland area of the sampled population occurring in each NNPI category was estimated at the scale of the conterminous US and within five large ecoregions and four broad wetland types. Potential stress from nonnative plants, as indicated by the NNPI category, was low for approximately 61% (similar to 15.3 million ha), moderate for about 20% (similar to 5.2 million ha), high for about 10% (similar to 2.48 million ha), and very high for about 9% (similar to similar to 2.2 million ha) of the wetland area in the entire sampled population. Percent of wetland area with high and very high NNPI varied by ecoregional subpopulations: greater within interior and western ecoregions (similar to 29 to 87%) than within ecoregions in the eastern half of the nation (similar to 11%). Among wetland type subpopulations, greater percent of wetland area with high and very high NNPI was observed for herbaceous vs. woody types and for inland vs. estuarine types. Estimates of wetland area by NNPI categories are expected to be useful to policy makers or resource managers for prioritizing management actions by identifying situations where stress from nonnative plants is most extensive. We also considered four exploratory analyses aimed at providing ecological information useful in interpreting NNPI extent results. We conducted three population-scale analyses examining ecoregional and wetland type population means for (1) the three NNPI metrics, (2) absolute cover of growth-habit groups of nonnative plants, and (3) metrics describing human-mediated disturbance. Finally, we examined ecological relationships with site-level NNPI status using a random forest (RF) analysis with NNPI as the response variable and predictor variables including ecoregion, wetland type, and a variety of characteristics describing natural vegetation structure, environment, and human-mediated disturbance.
机译:非植物被广泛认为是湿地和其他生态系统的压力源。它们可能与本土植物物种或社区竞争,并改变生态系统,这可能会影响生态条件,对资源管理人员构成挑战。作为美国环境保护局的国家湿地条件评估(NWCA)的一部分,我们在康瑟尔美国(美国)的湿地中的非湿地植物的地位。我们的主要目标是(1)文件于2011年的1138个NWCA网站的非舞台组成,(2)估计NWCA 2011年湿地的非型植物的压力下湿地的面积范围估计了2500万公顷的湿地(由967个采样概率站点和NWCA调查设计代表)。共有443个独特的非竞争标准塔,包括适应各种生态条件的物种池。对于个别地点,非竞争标准达的数量范围为0到29,而非含义的绝对覆盖率范围为0至160%。我们将非植物指标(NNPI)设计为来自在特定位置发生的集体非植物分类群的压力(低至非常高)的分类指标,基于非谐波,相对频率,相对频率的超标值的决策矩阵。和相对封面。在每个NNPI类别中发生的采样人口的湿地区域估计了孔雀石的规模,并在五种大型生态和四种广阔的湿地类型范围内估算。非植物的潜在压力,如NNPI类别所示,低约61%(类似于15.3亿公顷),中等约为20%(类似于520万公顷),高约10%(类似于248万HA),非常高,大约9%(类似于同样的湿地区域的湿地面积约9%(类似于220万公顷)。湿地面积的百分比和非常高的NNPI因常态群而变化:内部和西方eCoregions(类似于29〜87%)而不是国家的东部半部的生态(类似于11%)。在湿地型群中,对于草本与木质类型和内陆与河口类型,观察到具有高和非常高的NNPI的湿地区域的较高百分比。预计NNPI类别的湿地地区的估计值对于决策者或资源管理人员来说是有用的,以通过识别来自非植物的压力最广泛的情况来确定管理行动的优先考虑管理行动。我们还考虑了四次探索性分析,旨在提供有助于解释NNPI范围结果的生态信息。我们进行了三种人口标准分析,检查了(1)三个NNPI度量,(2)生长植物的生长习惯群体的绝对覆盖,(3)描述人介导的干扰的指标。最后,我们使用随机森林(RF)分析与NNPI分析为响应变量和预测变量的随机森林(RF)分析检查了与包括ECOREGION,湿地类型以及描述自然植被结构,环境和人类的各种特征的响应变量和预测变量的生态关系介导的干扰。

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