Linking Types of Rice Farming Systems to Farmers’ Perceptions of Complex Rice Systems

Abstract

CONTEXTComplex rice systems (CRS) are polycultures that combine indigenous knowledge and modern science in augmenting ecological processes to foster ecosystem services in rice agroecosystems. However, their implementation faces challenges due to farmer’s knowledge gaps, high capital outlay and labour shortages. OBJECTIVEThis study aims to link types of rice farming and farmer perceptions to facilitate recommendations to scale up CRS. METHODSWe constructed a farm typology based on 111 farm household surveys and aggregated cognitive maps (ACMs) based on fuzzy cognitive maps in focus group discussions in Malang and Lamongan, East Java Province, Indonesia. RESULTS AND CONCLUSIONSThe farm typology classified farm households into three types: (a) small farms with high inputs of agrochemicals (SH, n = 29) which were all identified in Malang; (b) medium-size farms with high input intensity of agrochemicals (MH, n = 43), distributed across Malang and Lamongan; and (c) medium-size farms with low inputs of agrochemicals (ML, n =39), all detected in Lamongan. ACMs revealed the differences of farmer group’s perceptions on CRS implementation. SH and MH farmers prioritised economic benefits over ecosystem services and crop-livestock components. SH farmers were locked into high-input and high-output systems, while MH farmers failed to obtain high output despite high input use. Intervention schemes could be developed such as thorough training on economics for SH farmers and efficient use and on-farm production of fertilisers for MH farmers. Meanwhile, with the majority of ML farmers having adopted CRS, their priorities were more evenly distributed across all components, implying their more holistic understanding of the interacted components. However, technical assistance, stakeholder collaboration and extension services were still considered to be needed to ensure a long-term sustainability of CRS practices by ML farmers. SIGNIFICANCECombining farm typology and fuzzy cognitive mapping could facilitate a comprehensive understanding of farming system types, their characteristics and their farmer’s perceptions as a key to more desirable outcomes of intervention formulation. Therefore, these methodological approaches provide guidance to accelerate transitions toward complex agroecosystem.

Keywords: Farm typology, fuzzy cognitive map, aggregated cognitive map, complex agroecosystems, technological adoption, intervention schemes.