Soil macrofauna diversity and structure under different management of pine-coffee agroforestry system - Cahyo Prayogo; Noegraha Sholehuddin; Eka Zainul Hasan Syahfinada Putra; Rina Rachmawati (Journal of Degraded and Mining Lands Management, 2019)
The role of tropical forests for maintaining environmental functions is decreasing due to the rapid changes to agricultural purposes. Agroforestry system is assumed to be an alternative system which reduces the negative impact of the conversion in term of maintaining the level of soil macrofauna diversity. This study was conducted at UB Forest within the period November 2017 to February 2018 by collecting soil macrofauna from 9 different land use types using hand sorting along with pitfall sampling for comparison. ANOVA and various diversity indexes were used (Shannon index, Pielu index, etc) to determine macrofauna structure and communities. Total soil C was examined using Walkley and Black method along with Particulate Organic Matter (POM) C fractionation approaches. Litter inputs were collected using a litter trap method, whilst in-situ litter were determined using destructive methods. Biplot and CVA multivariate analyses were adopted to determine the impact of different management on soil macrofauna diversity and structure. The result showed that conversion to agriculture practices reduced the structure, population and abundance of soil macrofauna as litter production, organic matter and soil C content decreased. The lowest abundance of individual soil macrofauna at monoculture system (PM) was reduced to 45 morphospecies compared to pine coffee agroforestry at the age of 4 (PK4:20 years after planting) system as much as 104 morphospecies. There was a strong relationship between litter thickness and the abundance of soil macrofauna. Both methods (Hand sorting vs Pitfalls traps), had a different ability for collecting soil macrofauna communities. Species occurs at rich or low organic matter input can be adopted as soil macrofauna bioindicator of changes on an ecosystem. Biplot and CVA methods can be used to distinguish and to cluster the impact of different management at various agroforestry systems.