Evaluating ecosystem services for agricultural wetlands: a systematic review and meta-analysis

湿地 生态系统服务 供应 生态系统 环境科学 农业 环境资源管理 人口 生产力 生态学 计算机科学 生物 经济 电信 人口学 宏观经济学 社会学
作者
Eric Asare,Mantyka-Pringle Chrystal,A. Beever Erik,Belcher Kenneth,Clark Robert
出处
期刊:Wetlands Ecology and Management [Springer Science+Business Media]
卷期号:30 (6): 1129-1149 被引量:19
标识
DOI:10.1007/s11273-022-09857-5
摘要

Abstract Globally, the extent of inland wetlands has declined by approximately 70% since the start of the twentieth century, resulting in the loss of important wetland-associated ecosystem services. We evaluate the drivers of wetland values in agricultural landscapes to increase the effectiveness and reliability of benefit transfer tools to assign values to local wetland services. We reviewed 668 studies that analyzed wetland ecosystem services within agricultural environments and identified 45 studies across 22 countries that provided sufficient economic information to be included in a quantitative meta-analysis. We developed meta-regression models to represent provisioning and regulating wetland ecosystem services and identify the main drivers of these ecosystem service categories. Provisioning wetland ecosystem service values were best explained (direction of effects in parenthesis) by high-income variable (+), peer-reviewed journal publications (+), agricultural total factor productivity index (−) and population density (+), while agricultural total factor productivity index (−), income level ( +) and wetland area (−) had significant effects on regulating wetland ecosystem service values. Our models can help estimate wetland values more reliably across similar regions because they have significantly lower transfer errors (66 and 185% absolute percentage error for the provisioning and regulating models, respectively) than the errors from unit value transfers. Model predicted wetland values ($/Ha/Year) range from $0.62 to $11,216 for regulating services and $0.95 to $2,122 for provisioning services and vary based on the differences in the levels of the variables (in the wetland locations) that best explained the estimated models.
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