Kearney Sean Patrick, Coops Nicholas C, Chan Kai M A, Fonte Steven J, Siles Pablo, Smukler Sean M
Faculty of Land and Food Systems, University of British Columbia, 2357 Main Mall, Vancouver, BC V6T 1Z4, Canada.
Department of Forest Resource Management, 2424 Main Mall, University of British Columbia, Vancouver, V6T 1Z4, Canada.
J Environ Manage. 2017 Nov 1;202(Pt 1):287-298. doi: 10.1016/j.jenvman.2017.07.039. Epub 2017 Jul 22.
Agroforestry management in smallholder agriculture can provide climate change mitigation and adaptation benefits and has been promoted as 'climate-smart agriculture' (CSA), yet has generally been left out of international and voluntary carbon (C) mitigation agreements. A key reason for this omission is the cost and uncertainty of monitoring C at the farm scale in heterogeneous smallholder landscapes. A largely overlooked alternative is to monitor C at more aggregated scales and develop C contracts with groups of land owners, community organizations or C aggregators working across entire landscapes (e.g., watersheds, communities, municipalities, etc.). In this study we use a 100-km agricultural area in El Salvador to demonstrate how high-spatial resolution optical satellite imagery can be used to map aboveground woody biomass (AGWB) C at the landscape scale with very low uncertainty (95% probability of a deviation of less than 1%). Uncertainty of AGWB-C estimates remained low (<5%) for areas as small as 250 ha, despite high uncertainties at the farm and plot scale (34-99%). We estimate that CSA adoption could more than double AGWB-C stocks on agricultural lands in the study area, and that utilizing AGWB-C maps to target denuded areas could increase C gains per unit area by 46%. The potential value of C credits under a plausible adoption scenario would range from $38,270 to $354,000 yr for the study area, or about $13 to $124 ha yr, depending on C prices. Considering farm sizes in smallholder landscapes rarely exceed 1-2 ha, relying solely on direct C payments to farmers may not lead to widespread CSA adoption, especially if farm-scale monitoring is required. Instead, landscape-scale approaches to C contracting, supported by satellite-based monitoring methods such as ours, could be a key strategy to reduce costs and uncertainty of C monitoring in heterogeneous smallholder landscapes, thereby incentivizing more widespread CSA adoption.
小农农业中的农林业管理能够带来缓解气候变化和适应气候变化的效益,并且已作为“气候智能型农业”(CSA)得到推广,但在国际和自愿碳减排协议中通常未被纳入。这一遗漏的一个关键原因是,在异质性小农景观的农场尺度上监测碳存在成本和不确定性。一个很大程度上被忽视的替代方案是在更综合的尺度上监测碳,并与跨越整个景观(如流域、社区、市镇等)的土地所有者群体、社区组织或碳聚合商签订碳合同。在本研究中,我们利用萨尔瓦多一个100公里的农业区域,展示了高空间分辨率光学卫星图像如何用于在景观尺度上绘制地上木质生物量(AGWB)碳,且不确定性非常低(偏差小于1%的概率为95%)。尽管在农场和地块尺度上不确定性很高(34 - 99%),但对于小至250公顷的区域,AGWB - C估计的不确定性仍然很低(<5%)。我们估计,采用CSA可使研究区域内农业土地上的AGWB - C储量增加一倍多,利用AGWB - C地图来确定裸露区域可使单位面积的碳增益提高46%。在一个合理的采用情景下,研究区域的碳信用潜在价值每年在38,270美元至354,000美元之间,即每公顷每年约13美元至124美元,具体取决于碳价格。考虑到小农景观中的农场规模很少超过1 - 2公顷,仅依靠直接向农民支付碳费用可能无法导致CSA的广泛采用,特别是如果需要进行农场尺度监测的话。相反,由我们这样的基于卫星的监测方法支持的景观尺度碳合同方法,可能是降低异质性小农景观中碳监测成本和不确定性的关键策略,从而激励更广泛地采用CSA。