Towards data-driven tropical forest restoration: Uncovering spatial variation, interactions and historical management effects on nutrients along soil depth gradients

Abstract

Data scarcity hinders global conservation initiatives, and there is a pressing demand for spatially detailed soil and species data to restore human-altered tropical forests. We, therefore, aimed to generate foundational soil environment and habitat suitability data and high-resolution soil maps to aid restoration efforts in a critical ecosystem of the threatened Indo-Burma Biodiversity Hotspot region, i.e., Tarap Hill Reserve (THR) in Bangladesh. Using multiple soil depths and vegetation data, we answered three major questions. (QI) How do spatial distribution and the relationships between soil physicochemical properties (i.e., pH, sand, silt, and clay percentages, organic carbon, and nutrients – N, P, K, Ca, Mg, Fe, and Zn) vary from surface to deeper soils (top 1 m)? (QII) How do different forest management interventions, i.e., old-growth forests (OGF), mixed plantations (MXP), and mono-specific plantations (MOP), influence soil properties, nutrients, and carbon in different soil depths? (QIII) Which spatial interpolation methods are best suited for making more accurate soil property predictions at different depths? Our analyses reveal decreasing availability of critical nutrients like N, P, Mg, and Fe from surface to subsurface soils, while pH, soil organic carbon, and clay content increased with depth. Several soil properties showed significant interactions, although the strength of the interactions changed from surface to deeper soils. Besides, forest management interventions significantly influenced soil functionality by having higher nutrient availability and soil organic carbon in OGF than MXP and MOP. Predictive performances of the deterministic and geostatistical interpolation methods varied for different soil properties in different soil depths, and soil maps revealed substantial heterogeneity in the distribution of soil properties across space and along depths. This study represents a pioneering step in data-driven tropical forest restoration, and our novel findings and high-resolution soil maps could guide future studies focusing on species habitat preferences, restoration ecology, and spatial conservation planning in the Indo-Burma Biodiversity Hotspot region and elsewhere in the tropics.