Understanding relationships among ecosystem services across spatial scales and over time

环境科学 生态系统服务 分水岭 空间生态学 地表径流 时间尺度 生态系统 环境资源管理 空间变异性 比例(比率) 生态学 水文学(农业) 地理 计算机科学 数学 统计 地图学 岩土工程 机器学习 工程类 生物
作者
Jiangxiao Qiu,Stephen R. Carpenter,Eric G. Booth,Melissa Motew,Samuel C. Zipper,Christopher J. Kucharik,Steven P. Loheide,Monica G. Turner
出处
期刊:Environmental Research Letters [IOP Publishing]
卷期号:13 (5): 054020-054020 被引量:100
标识
DOI:10.1088/1748-9326/aabb87
摘要

Sustaining ecosystem services (ES), mitigating their tradeoffs and avoiding unfavorable future trajectories are pressing social-environmental challenges that require enhanced understanding of their relationships across scales. Current knowledge of ES relationships is often constrained to one spatial scale or one snapshot in time. In this research, we integrated biophysical modeling with future scenarios to examine changes in relationships among eight ES indicators from 2001–2070 across three spatial scales—grid cell, subwatershed, and watershed. We focused on the Yahara Watershed (Wisconsin) in the Midwestern United States—an exemplar for many urbanizing agricultural landscapes. Relationships among ES indicators changed over time; some relationships exhibited high interannual variations (e.g. drainage vs. food production, nitrate leaching vs. net ecosystem exchange) and even reversed signs over time (e.g. perennial grass production vs. phosphorus yield). Robust patterns were detected for relationships among some regulating services (e.g. soil retention vs. water quality) across three spatial scales, but other relationships lacked simple scaling rules. This was especially true for relationships of food production vs. water quality, and drainage vs. number of days with runoff >10 mm, which differed substantially across spatial scales. Our results also showed that local tradeoffs between food production and water quality do not necessarily scale up, so reducing local tradeoffs may be insufficient to mitigate such tradeoffs at the watershed scale. We further synthesized these cross-scale patterns into a typology of factors that could drive changes in ES relationships across scales: (1) effects of biophysical connections, (2) effects of dominant drivers, (3) combined effects of biophysical linkages and dominant drivers, and (4) artificial scale effects, and concluded with management implications. Our study highlights the importance of taking a dynamic perspective and accounting for spatial scales in monitoring and management to sustain future ES.
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