Data to: Acoustic indices as proxies for biodiversity in certified and non-certified cocoa plantations in Indonesia

Acoustic indices allow time efficient analysis of large acoustic datasets obtained from passive acoustic monitoring, but results regarding their effectiveness in assessing biodiversity are inconsistent. We evaluated the efficacy of six acoustic indices (ACI, ADI, AEI, H, BI, NDSI) for studying bird and structural diversity in 51 cocoa plantations, 24 of which were certified by Rainforest Alliance, in Luwu Timur, Sulawesi, Indonesia. We used linear models to assess the correlation of index values with bird species richness, and linear mixed models to test the influence of canopy closure, shade tree basal area, distance to primary forest and tree cover in a 200 m buffer on index values. Bird species richness was positively correlated with BI (p = 0.02) and negatively with H (p = 0.03), yet predictive power was low (R² = 0.10 and 0.09, respectively). Acoustic indices did not differ significantly for certified cocoa plantations. Tree cover within the 200 m buffer moderately well predicted ACI values (marginal R² = 0.37) while for the other indices effect sizes were low or correlations were not significant. Comparing our results to other studies, acoustic indices may reflect biodiversity across land uses, but were of limited value for tracking subtle differences in cocoa plantations in Sulawesi. Future studies may include more land uses (i.e., rice paddies, secondary forest, oil palm) as well as more taxa (i.e., insects). More research is needed on the comparability of acoustic indices, as we found them to be influenced by recording equipment and calculation settings.声学指数（acoustic indices）可实现对被动声学监测（passive acoustic monitoring）获取的大规模声学数据集的高效分析，但现有研究关于其在生物多样性评估中的有效性结论并不统一。本研究以印度尼西亚苏拉威西岛东卢武（Luwu Timur）地区的51处可可种植园为研究对象，其中24处已通过雨林联盟（Rainforest Alliance）认证，旨在评估6种声学指数（ACI、ADI、AEI、H、BI、NDSI）在探究鸟类多样性与结构多样性方面的效能。研究采用线性模型分析各指数值与鸟类物种丰富度的相关性，并运用线性混合模型（linear mixed models）检验林冠郁闭度、遮荫树断面积、到原生林的距离以及200米缓冲区（200 m buffer）内树木覆盖率对声学指数值的影响。结果显示，鸟类物种丰富度与BI呈显著正相关（p=0.02），与H呈显著负相关（p=0.03），但二者的预测能力均较低（决定系数R²分别为0.10与0.09）。经认证的可可种植园的声学指数无显著差异。200米缓冲区的树木覆盖率可较好地预测ACI值（边际决定系数marginal R²=0.37），其余指数的效应量均较低，或相关性未达显著水平。将本研究结果与其他同类研究对比可知，声学指数或可反映不同土地利用类型下的生物多样性，但用于追踪苏拉威西岛可可种植园的细微差异时价值有限。未来研究可纳入更多土地利用类型（如稻田、次生林、油棕种植园）以及更多生物类群（如昆虫）。此外，本研究发现声学指数受录音设备与计算参数设置的影响，因此亟需开展更多关于声学指数可比性的相关研究。