TITLE:
Observation-Oriented Causal Discovery for Cultivation Abandonment of Rice Terraces: Focusing on an Effect of Cultural Endemism on Decision-Making in Toraja, Indonesia
AUTHORS:
Ayako Oide, Osamu Kozan, Tomoko Doko, Wenbo Chen
KEYWORDS:
Cultivation Abandonment, Decision-Making, Rice Terrace, Observation-Oriented, Multivariate Logistic Regression, Sub-Group, Interaction, InSAR, Soil Erosion, GIS
JOURNAL NAME:
Agricultural Sciences,
Vol.7 No.2,
February
24,
2016
ABSTRACT: Previous discussion about the factors of the expanding trend of abandoned cultivation had focused only on universal factors and lacked evaluation of the regionality of the phenomenon. This paper demonstrated the Toraja’s regional characteristics and the influence of cultural endemism on decision-making about abandoning cultivation by an observation-oriented approach. Based on a causal framework constructed by field observation and geospatial data generation, an adjustment for overt covariates using the multivariate logistic regression model to draw the causal effect from hidden covariates was examined in two rice terraces with different water systems, i.e. irrigated field and rain-fed field. The result of sub-group analysis revealed that decisions about abandoning cultivation in Toraja were greatly associated with disadvantageous factors for intensive farming, i.e. “number of adjacent fields” and “soil erosion” rather than advantageous factors, i.e. “area of field” and “distance to roads”. Moreover, the result of interaction analysis which controlled the effect of topography revealed the powerful effect of particular decision factors only in rain-fed rice terrace: the “distance to roads” factor’s fairly negative contribution on abandoning cultivation (Odds ratio = 9.94E -01, P value = 2.03E- 11), as well as the “number of adjacent field” factor’s positive contribution on abandoning cultivation (Odds ratio = 1.13E+00, P value = 3.65E- 04). Given the evidence from the explanation of these results by customary laws and land inheritance system for each site, therefore, it could be concluded that the screening and detection of cultural endemism’s influence was achieved using the algorithm this paper proposes.