Monitoring ecosystem functions in mountain catchments of chilean patagonia: A cluster-based dataset

This dataset documents the spatially explicit quantification of multiple ecosystem functions across 12 mountain headwater catchments in the Aysén Region of Chilean Patagonia. Designed to capture landscape variability, the observational framework employs a paired-catchment approach, comparing basins with different degrees of anthropogenic disturbance across two forest types: deciduous and evergreen. Each catchment is treated as an integrated landscape unit, with cluster-based field measurements capturing fine-scale variation in vegetation structure, biomass, soil conditions, and species richness. The field inventory integrates and adapts methodologies from several national and international forest monitoring frameworks. Its core structure is based on Chile’s Continuous National Forest Inventory, but also incorporates sampling concepts and measurement protocols inspired by the Swiss National Forest Inventory (LFI), the U.S. Forest Inventory and Analysis (FIA) program, and long-term ecological monitoring plots used in New Zealand. This hybrid design ensures multidimensional assessment of ecosystem functions while enhancing cross-regional comparability. The sampling design addresses ecosystem functions across four service categories: provisioning (sawlog and firewood volume), regulating (carbon stocks in trees, shrubs, and deadwood, and decadal sequestration rates), supporting (soil formation and erosion proxies, plus nutrient concentrations), and biodiversity maintenance (vascular plant and epiphyte). This dataset supports ecological synthesis, spatial modeling, and integration into broader assessments of ecosystem services and land-use impacts under changing environmental conditions.

• Publication year

  2026

• Venue

  Data in Brief

• Publication date

  2026-01-01

• Fields of study

  Medicine, Environmental Science

• Identifiers
  DOI 10.1016/j.dib.2026.112481PMID 41646522PMCID 12870798
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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