...
首页> 外文期刊>Ecological Applications >Wetland features and landscape context predict the risk of wetland habitat loss
【24h】

Wetland features and landscape context predict the risk of wetland habitat loss

机译:湿地特征和景观环境可预测湿地生境丧失的风险

获取原文
获取原文并翻译 | 示例

摘要

Wetlands generally provide significant ecosystem services and function as important harbors of biodiversity. To ensure that these habitats are conserved, an efficient means of identifying wetlands at risk of conversion is needed, especially in the southern United States where the rate of wetland loss has been highest in recent decades. We used multivariate adaptive regression splines to develop a model to predict the risk of wetland habitat loss as a function of wetland features and landscape context. Fates of wetland habitats from 1992 to 1997 were obtained from the National Resources Inventory for the U.S. Forest Service's Southern Region, and land-cover data were obtained from the National Land Cover Data. We randomly selected 70% of our 40 617 observations to build the model (n 1/4 28 432), and randomly divided the remaining 30% of the data into five Test data sets (n 1/4 2437 each). The wetland and landscape variables that were important in the model, and their relative contributions to the model's predictive ability (100 1/4 largest, 0 1/4 smallest), were land-cover/land-use of the surrounding landscape (100.0), size and proximity of development patches within 570 m (39.5), land ownership (39.1), road density within 570 m (37.5), percent woody and herbaceous wetland cover within 570 m (27.8), size and proximity of development patches within 5130 m (25.7), percent grasslands/herbaceous plants and pasture/hay cover within 5130 m (21.7), wetland type (21.2), and percent woody and herbaceous wetland cover within 1710 m (16.6). For the five Test data sets, Kappa statistics (0.40, 0.50, 0.52, 0.55, 0.56; P, 0.0001), area-under-the-receiver-operating-curve (AUC) statistics (0.78, 0.82, 0.83, 0.83, 0.84; P, 0.0001), and percent correct prediction of wetland habitat loss (69.1, 80.4, 81.7, 82.3, 83.1) indicated the model generally had substantial predictive ability across the South. Policy analysts and land-use planners can use the model and associated maps to prioritize at-risk wetlands for protection, evaluate wetland habitat connectivity, predict future conversion of wetland habitat based on projected land-use trends, and assess the effectiveness of wetland conservation programs.
机译:湿地通常提供重要的生态系统服务,并起着重要的生物多样性港口的作用。为了确保这些栖息地得到保护,需要一种有效的方法来识别有转化风险的湿地,尤其是在美国南部,这是近几十年来湿地流失率最高的地区。我们使用多元自适应回归样条建立了一个模型,以预测湿地栖息地丧失的风险与湿地特征和景观环境的关系。 1992年至1997年的湿地栖息地命运是从美国森林服务局南部地区国家资源清单获得的,土地覆盖数据是从国家土地覆盖数据中获得的。我们从40 617个观测值中随机选择70%来构建模型(n 1/4 28 432),并将剩余的30%数据随机分为五个测试数据集(每个n 1/4 2437)。模型中重要的湿地和景观变量及其对模型的预测能力的相对贡献(最大100 1/4,最小0 1/4)是周围景观的土地覆盖/土地利用(100.0) ,570 m(39.5)之内的开发斑块的大小和距离,土地所有权(39.1),570 m(37.5)内的道路密度,570 m(27.8)内的木质和草本湿地覆盖率,5130范围内的开发斑块m(25.7),5130 m(21.7)内的草地/草皮植物和牧场/干草的百分比,湿地类型(21.2)和1710 m(16.6)内的木本和草本湿地覆盖率。对于这五个测试数据集,Kappa统计量(0.40、0.50、0.52、0.55、0.56; P,0.0001),接收者操作曲线下面积(AUC)统计量(0.78、0.82、0.83、0.83、0.84 ; P,0.0001)和对湿地栖息地丧失的正确预测百分比(69.1、80.4、81.7、82.3、83.1)表明,该模型在整个南部地区通常具有实质性的预测能力。政策分析人员和土地利用规划人员可以使用模型和相关地图来优先考虑处于风险中的湿地以进行保护,评估湿地栖息地的连通性,根据预计的土地利用趋势预测未来湿地栖息地的转换以及评估湿地保护计划的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号