4.1 Article

Predicted risks of groundwater decline in seasonal wetland plant communities depend on basin morphology

期刊

WETLANDS ECOLOGY AND MANAGEMENT
卷 26, 期 3, 页码 359-372

出版社

SPRINGER
DOI: 10.1007/s11273-017-9578-3

关键词

Groundwater-dependent ecosystem; Plant functional group; Predictive model; Wetland bathymetry; Wetland monitoring; Wetland typology

资金

  1. Goyder Water Research Institute [E.2.5]

向作者/读者索取更多资源

In regions of the world where the climate is expected to become drier, meeting environmental water needs for wetlands and other dependent ecosystems will become increasingly challenging. Ecological models can play an important role, by quantifying system responses to reduced water availability and predicting likely ecological impacts. Anticipating these changes can inform both conservation and monitoring effort. We used water-plant functional group models to predict the effects of a declining water table for two wetland types reliant on the surface expression of groundwater but of contrasting basin morphology. Our interest was in quantifying the relative sensitivity of these wetland types to different amounts of groundwater decline. For the shallower, grass-sedge wetland, terrestrial plant probabilities increased markedly for declines between 0.25 and 0.5 m, but amphibious and submerged functional groups changed predictably, or not at all. However, mean inundated area reduced by over 70% for a 0.5 m groundwater decline, suggesting loss of area posed the greatest risk in this wetland type. In the deeper, steep-sided interdunal wetland, inundated area changed little, but models suggest clear transitions in plant functional group composition. Sedge-group probabilities increased sharply for declines between 0.25 and 0.5 m, while declines between 0.5 and 1.0 m predicted the loss of submerged species. As might be anticipated, the risks associated with groundwater level decline depend on basin morphology. However, by quantifying probable ways in which this will manifest in different wetland types, model predictions improve our ability to recognise and manage change.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.1
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据