Landscape, welfare, and distributional trade-offs from smallholder agroforestry contracting: An agent-based model approach

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems Pub Date : 2025-08-29 DOI:10.1016/j.agsy.2025.104493

Daniel Hill, Oscar Cacho, Jonathan Moss

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引用次数: 0

Abstract

CONTEXT

Agroforestry value chains have been extensively promoted as potential ‘win-win’ vehicles for Sustainable Intensification in tropical upland landscapes. Coffee contract farming in particular can support landscape environmental policy objectives through improvements in soil erosion and biomass carbon, while also providing smallholders with higher agricultural profits.

OBJECTIVE

This paper explores the extent in which coffee agroforestry contract farming influences household welfare and landscape environmental outcomes using a case study of the peri-urban uplands of Bandung, Indonesia.

METHODS

We develop an agent-based simulation model to test the welfare and landscape effects of coffee contracting interventions. The model incorporates household survey data with granular land cover and soil maps. Smallholder farmer agents interact with coffee value chains and other agricultural and labour markets, and make land use decisions that have landscape-level environmental and household welfare implications.

RESULTS AND CONCLUSIONS

The modelling simulations show that coffee contracting can achieve improved incomes for farmers, and increased agroforestry landcover. However, transaction costs can impede many households from accessing contract coffee markets, resulting in trade-offs between higher incomes and increasing rural income inequality. Contract coffee displaces lower-input agroforestry where opportunity costs are low, resulting in significant landscape declines in biomass carbon and increases in soil erosion – an outcome akin to a Jevon's Paradox.

SIGNIFICANCE

Agroforestry value chain interventions deliver trade-offs when seeking to address multiple and complex landscape challenges. Complementary non-market interventions that better align smallholder incentives with environmental policy objectives are necessary for these value chain interventions to be effective tools for Sustainable Intensification.

Abstract Image

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小农农林业承包的景观、福利和分配权衡：基于主体的模型方法

农林业价值链已被广泛推广为热带高地景观可持续集约化的潜在“双赢”工具。咖啡合同农业尤其可以通过改善土壤侵蚀和生物量碳来支持景观环境政策目标，同时也为小农提供更高的农业利润。目的：本文以印度尼西亚万隆城郊高地为例，探讨咖啡农林承包农业对家庭福利和景观环境结果的影响程度。方法建立基于主体的模拟模型，检验咖啡承包干预的福利和景观效应。该模型将住户调查数据与颗粒状土地覆盖和土壤图结合起来。小农代理人与咖啡价值链以及其他农业和劳动力市场互动，并做出具有景观层面环境和家庭福利影响的土地使用决策。结果与结论模型模拟表明，咖啡承包可以提高农民的收入，增加农林业土地覆盖。然而，交易成本可能阻碍许多家庭进入合同咖啡市场，导致收入增加与农村收入不平等加剧之间的权衡。合同咖啡取代了机会成本较低的低投入农林业，导致生物质碳的显著景观下降和土壤侵蚀的增加——类似于杰文悖论的结果。林业价值链干预措施在寻求解决多重和复杂的景观挑战时提供了权衡。要使这些价值链干预措施成为可持续集约化的有效工具，就必须采取补充性的非市场干预措施，使小农的激励措施与环境政策目标更好地结合起来。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Agricultural Systems 农林科学-农业综合

CiteScore

13.30

自引率

7.60%

发文量

174

审稿时长

30 days

期刊介绍： Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments. The scope includes the development and application of systems analysis methodologies in the following areas: Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making; The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment; Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems; Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.