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Forecasting climate change impacts on the distribution of wetland habitat in the Midwestern United states

机译:预测气候变化对美国中西部湿地栖息地分布的影响

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Shifting precipitation patterns brought on by climate change threaten to alter the future distribution of wetlands. We developed a set of models to understand the role climate plays in determining wetland formation on a landscape scale and to forecast changes in wetland distribution for the Midwestern United States. These models combined 35 climate variables with 21 geographic and anthropogenic factors thought to encapsulate other major drivers of wetland distribution for the Midwest. All models successfully recreated a majority of the variation in current wetland area within the Midwest, and showed that wetland area was significantly associated with climate, even when controlling for landscape context. Inferential (linear) models identified a consistent negative association between wetland area and isothermality. This is likely the result of regular inundation in areas where precipitation accumulates as snow, then melts faster than drainage capacity. Moisture index seasonality was identified as a key factor distinguishing between emergent and forested wetland types, where forested wetland area at the landscape scale is associated with a greater seasonal variation in water table depth. Forecasting models (neural networks) predicted an increase in potential wetland area in the coming century, with areas conducive to forested wetland formation expanding more rapidly than areas conducive to emergent wetlands. Local cluster analyses identified Iowa and Northeastern Missouri as areas of anticipated wetland expansion, indicating both a risk to crop production within the Midwest Corn Belt and an opportunity for wetland conservation, while Northern Minnesota and Michigan are potentially at risk of wetland losses under a future climate.
机译:气候变化带来的不断变化的降水模式有可能改变湿地的未来分布。我们开发了一组模型,以了解气候在景观规模上确定湿地形成的作用,并预测美国中西部湿地分布的变化。这些模型将35个气候变量与21个地理和人为因素结合在一起,认为它们封装了中西部湿地分布的其他主要驱动因素。所有模型成功地重建了中西部当前湿地面积的大部分变化,并表明即使控制景观环境,湿地面积也与气候显着相关。推论(线性)模型确定了湿地面积与等温性之间的一致负相关性。这可能是由于在积雪随雪积聚,然后融化快于排水能力的地区经常被淹没的结果。水分指数的季节性被确定为区分新兴湿地和森林湿地类型的关键因素,其中景观尺度上的森林湿地面积与地下水位深度的较大季节性变化有关。预测模型(神经网络)预测,下个世纪潜在湿地面积将增加,有利于森林湿地形成的区域比有利于新兴湿地的区域增长更快。局部聚类分析将爱荷华州和密苏里州东北地区视为预期的湿地扩展区,这表明中西部玉米带内的作物生产风险和湿地保护的机会,而明尼苏达州北部和密歇根州在未来气候下可能面临湿地丧失的风险。

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