生态系统服务
景观生态学
自然保护
环境资源管理
人类生态系统总量
可持续发展
景观评价
地理
环境规划
生态系统
生态学
景观设计
生态系统健康
环境科学
栖息地
生物
作者
Gabriela Teixeira Duarte,Paloma Marques Santos,Tatiana Cornelissen,Milton Cézar Ribeiro,Adriano Pereira Paglia
出处
期刊:Landscape Ecology
[Springer Science+Business Media]
日期:2018-06-25
卷期号:33 (8): 1247-1257
被引量:201
标识
DOI:10.1007/s10980-018-0673-5
摘要
The recently introduced concept of ‘landscape services’—ecosystem services influenced by landscape patterns—may be particularly useful in landscape planning by potentially increasing stakeholder participation and financial funding. However, integrating this concept remains challenging. In order to bypass this barrier, we must gain a greater understanding of how landscape composition and configuration influence the services provided. We conducted meta-analyses that considered published studies evaluating the effects of several landscape metrics on the following services: pollination, pest control, water quality, disease control, and aesthetic value. We report the cumulative mean effect size (E++), where the signal of the values is related to positive or negative influences. Landscape complexity differentially influenced the provision of services. Particularly, the percentage of natural areas had an effect on natural enemies (E++ = 0.35), pollination (E++ = 0.41), and disease control (E++ = 0.20), while the percentage of no-crop areas had an effect on water quality (E++ = 0.42) and pest response (E++ = 0.33). Furthermore, heterogeneity had an effect on aesthetic value (E++ = 0.5) and water quality (E++ = − 0.40). Moreover, landscape aggregation was important to explaining pollination (E++ = 0.29) and water quality (E++ = 0.35). The meta-analyses reinforce the importance of considering landscape structure in assessing ecosystem services for management purposes and decision-making. The magnitude of landscape effect varies according to the service being studied. Therefore, land managers must account for landscape composition and configuration in order to ensure the maintenance of services and adapt their approach to suit the focal service.
科研通智能强力驱动
Strongly Powered by AbleSci AI