...
首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Modelling local distribution of an Arctic dwarf shrub indicates an important role for remote sensing of snow cover
【24h】

Modelling local distribution of an Arctic dwarf shrub indicates an important role for remote sensing of snow cover

机译:对北极矮灌木的局部分布进行建模表明了对积雪遥感的重要作用

获取原文
获取原文并翻译 | 示例

摘要

Despite the intensive research effort directed at predicting the effects of climate change on plants in the Arctic, the impact of environmental change on species' distributions remains difficult to quantify. Predictive habitat distribution models provide a tool to predict the geographical distribution of a species based on the ecological gradients that determine it, and to estimate how the distribution of a species might respond to environmental change. Here, we present a model of the distribution of the dwarf shrub Dryas octopetala L. around the fjord Kongsfjorden, Svalbard. The model was built from field observations, an Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) image, a GIs database containing environmental data at a spatial resolution of 20 m, and relied on generalized linear models (GLMs). We used a logistic GLM to predict the occurrence of the species and a Gaussian GLM to predict its abundance at the sites where it occurred. Temperature and topographical exposure and inclination of a site appeared to promote both the occurrence and the abundance of D. octopetala. The occurrence of the species was additionally negatively influenced by snow and water cover and topographical exposure towards the north, whereas the abundance of the species appeared lower on calciferous substrates. Validation of the model using independent data and the resulting distribution map showed that they successfully recover the distribution of D. octopetala in the study area (kappa = 0.46, AUC =0.81 for the logistic GLM [n - 200], r(2) = 0.29 for the Gaussian GLM [n - 36]). The results further highlight that models predicting the local distribution of plant species in an Arctic environment would greatly benefit from data on the distribution and duration of snow cover. Furthermore, such data are necessary to make quantitative estimates for the impact of changes in temperature and winter precipitation on the distribution of plants in the Arctic. (C) 2005 Elsevier Inc. All rights reserved.
机译:尽管进行了大量的研究工作以预测北极地区气候变化对植物的影响,但环境变化对物种分布的影响仍然难以量化。可预测的栖息地分布模型提供了一种工具,可根据确定该物种的生态梯度来预测该物种的地理分布,并估算该物种的分布可能如何响应环境变化。在这里,我们介绍了斯瓦尔巴群岛的峡湾孔斯菲约登周围矮灌木树蛙(Dryas octopetala L.)的分布模型。该模型是根据现场观察,先进的星载热发射和反射辐射计(ASTER)图像,包含空间分辨率为20 m的环境数据的GIs数据库建立的,并依赖于广义线性模型(GLM)。我们使用逻辑GLM预测物种的发生,并使用高斯GLM预测物种发生地点的丰度。温度和地形的暴露以及部位的倾斜似乎促进了八爪D的发生和数量的增加。该物种的出现还受到积雪和水的覆盖以及向北的地形暴露的负面影响,而该物种的丰富度在钙质基质上显得较低。使用独立数据和所得分布图对模型进行的验证表明,他们成功地恢复了研究区八爪鱼的分布(对于逻辑GLM [n-200],kappa = 0.46,AUC = 0.81,r(2)=高斯GLM [n-36]为0.29)。结果进一步强调,预测北极环境中植物物种局部分布的模型将大大受益于积雪分布和持续时间的数据。此外,这些数据对于定量估计温度和冬季降水对北极植物分布的影响是必要的。 (C)2005 Elsevier Inc.保留所有权利。

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