.png){kind=icon}
返回
Mapping landscape connectivity for large spatial extents
.png){kind=icon}
PRE
AI
DOI：10.1007/s10980-019-00897-6.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Context Mapping landscape connectivity across large spatial extents is an important component of ecological reserve network designs and species recovery plans. It can, however, be limited by computational power. One way to overcome this problem is to split the study area into smaller tiles, map landscape connectivity within each of those tiles, and then merge tiles back together to form composite connectivity maps. Objectives We tested the effects of landscape structure on the accuracy of composite landscape connectivity maps created from tiles and tested two methods to increase this accuracy. Methods We correlated replicate, composite current density maps with untiled maps. We tested whether our findings depended on the composition of the landscape by testing maps with corridors, barriers, different mixtures of high- and low-cost habitat, and road networks. Results We found that composite current density maps underestimated large-scale connectivity and overestimated the contribution of small habitat patches to overall connectivity. These biases became more pronounced as the tiles became relatively smaller. Landscapes with corridors or barriers were particularly sensitive. We increased the accuracy of tiled maps by increasing pixel size or by averaging several maps created using a moving window approach. Conclusions There is a trade-off between tile size and pixel size when modelling connectivity across large spatial extents. We suggest using the largest tile size possible when tiling is necessary, in conjunction with increased pixel size and a moving window method to increase accuracy of the composite current density maps.
Keyword:
Circuitscape
Connectivity
Moving window
Tile size
Tiling
Resolution
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.7
论文数:
3.8K
被引数:
1.4W
机构
引用论文
Functional connectivity of lynx at their southern range periphery in Ontario, Canada.png)
LANDSCAPE ECOLOGY
LANDSCAPE ECOLOGYIF3.7
PREAI
分享收藏Realistic levels of inbreeding depression strongly affect extinction risk in wild populations近交萧条的现实水平强烈影响野生种群的灭绝风险
PREAI
分享收藏Bounded Error Estimation: A Chebyshev Center Approach2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive ProcessingIF0
PREAI
分享收藏Connecting models to movements: testing connectivity model predictions against empirical migration and dispersal dataLANDSCAPE ECOLOGY
LANDSCAPE ECOLOGYIF3.7
PREAI
分享收藏Bilateral Cochlear Implants in Children: Localization Acuity Measured with Minimum Audible Angle
OAAI
OAAI分享收藏
查看更多内容