首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   2篇
  免费   0篇
园艺   2篇
  2019年   1篇
  2016年   1篇
排序方式: 共有2条查询结果,搜索用时 15 毫秒
1
1.
Context

Worldwide, anthropogenic habitat loss and degradation have led to substantial biodiversity declines. Preserving biodiversity requires an understanding of how habitat loss and degradation interact to impact species populations, and how land-use decisions can limit these losses.

Objectives

We present a mathematical partitioning of changes in landscape-level population abundance in response to land-use change using a modified version of the Price equation from evolutionary biology.

Methods

The Price equation partitions changes in species abundance into multiple drivers related to habitat loss, habitat degradation, and their interaction. We describe its development and exemplify its applicability using simulated data.

Results

Applying the Price equation to simulated data reveals the roles of habitat loss, habitat degradation, and their interaction in driving population change in patchy landscapes undergoing complex land-use change processes.

Conclusions

The Price equation is a theoretical tool that may enhance our understanding of the effects of land-use change on populations by accounting for the specific processes by which land-use change operates across landscapes.

  相似文献   
2.

Context

Wildfires destroy thousands of buildings every year in the wildland urban interface. However, fire typically only destroys a fraction of the buildings within a given fire perimeter, suggesting more could be done to mitigate risk if we understood how to configure residential landscapes so that both people and buildings could survive fire.

Objectives

Our goal was to understand the relative importance of vegetation, topography and spatial arrangement of buildings on building loss, within the fire’s landscape context.

Methods

We analyzed two fires: one in San Diego, CA and another in Boulder, CO. We analyzed Google Earth historical imagery to digitize buildings exposed to the fires, a geographic information system to measure some of the explanatory variables, and FRAGSTATS to quantify landscape metrics. Using logistic regression we conducted an exhaustive model search to select the best models.

Results

The type of variables that were important varied across communities. We found complex spatial effects and no single model explained building loss everywhere, but topography and the spatial arrangement of buildings explained most of the variability in building losses. Vegetation connectivity was more important than vegetation type.

Conclusions

Location and spatial arrangement of buildings affect which buildings burn in a wildfire, which is important for urban planning, building siting, landscape design of future development, and to target fire prevention, fuel reduction, and homeowner education efforts in existing communities. Landscape context of buildings and communities is an important aspect of building loss, and if taken into consideration, could help communities adapt to fire.
  相似文献   
1
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号