Santa Cruz island time series vegetation data

Methods
This dataset was collected as part of a long-term vegetation monitoring program on Santa Cruz Island, California, USA, following the removal of non-native grazers. Sampling was conducted across 100 30 x 2 m plots representing a range of plant communities (oak woodland, chaprral, pine, grassland, coastal scrub), restoration histories and management strategies.
Field Methods:Vegetation surveys were conducted annually during peak biomass (typically between March and May). Within each plot, species presence and cover were recorded using a modified point-intercept method along permanent transects. Each transect consisted of a standardized number of regularly spaced points where all hits were identified to species when possible.
Environmental Data:In addition to vegetation data, abiotic variables such as slope, aspect, soil type, and elevation were recorded for each plot using GPS, topographic maps, and field observations. Climatic data were interpolated from nearby weather stations a..., , # Santa Cruz island time series vegetation data

Dataset DOI: [10.5061/dryad.2fqz61327](10.5061/dryad.2fqz61327)

## Description of the data and file structure

**README – Santa Cruz Island Post-Grazing Vegetation Monitoring Dataset**

### **Data Description**

This dataset was collected as part of a long-term ecological monitoring effort to assess the recovery of native grassland vegetation following the removal of non-native herbivores on Santa Cruz Island, California. The goal of the project is to track plant community composition, diversity, and structural changes over time in response to grazing removal, restoration treatments, and ongoing management.

Sampling was conducted across a network of permanent plots representing varied environmental conditions and restoration histories. These data support analyses of vegetation recovery trajectories, treatment effectiveness, and spatial variation in community assembly.

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### **Methods Summary**

Vegetation surveys were conducted annu...,