TreeMapper

Setting Up Monitoring Plots

Learn how to establish and manage monitoring plots for long-term forest research and tracking.

Monitoring Plots in TreeMapper are designed to help restoration teams systematically monitor a defined area over time. They enable users to assess how forests and landscapes change as a result of restoration activities and to compare areas with and without interventions.

Monitoring plots provide a structured way to track plant growth, survival, and environmental conditions, supporting long-term, evidence-based restoration monitoring.

What Is a Monitoring Plot?

A monitoring plot represents a specific, clearly defined area within a restoration site that is observed repeatedly over time. By collecting consistent data from the same area, users can understand trends in vegetation growth, species composition, and ecosystem recovery.

Monitoring plots are particularly useful for:

  • Measuring the effectiveness of restoration interventions
  • Comparing restored areas with untouched or naturally regenerating areas
  • Generating reliable, long-term monitoring data

Creating a Monitoring Plot

To create a monitoring plot, users complete a simple registration form. This form captures three key aspects:

1. Plot Type

Users select whether the plot is an Intervention or a Control plot:

  • Intervention plots are areas where restoration activities (such as planting or assisted regeneration) have taken place.
  • Control plots represent areas without interventions and are used as reference points for comparison.

2. Plot Details

Users define the basic characteristics of the plot, such as its name and dimensions. This ensures that the plot can be consistently revisited and monitored over time.

3. Location

The plot's geographic location is recorded so that it can be accurately mapped, revisited, and visualized within the platform.

Once these steps are completed, the monitoring plot is registered and ready for data collection.

Adding Plants to a Monitoring Plot

After a plot is created, users can add plant-level data within the plot area.

For each plant, users record:

  • Whether the plant was planted or is a recruit (naturally occurring)
  • The Species
  • Initial measurements (such as height or diameter)
  • Optional tags for identification or grouping
  • The plant's position within the plot

This allows the plot to capture both restoration efforts and natural regeneration in a single monitoring framework.

Plant Timeline and Remeasurements

Plants within a monitoring plot can be observed repeatedly over time through a plant timeline.

As monitoring continues, users can:

  • Add new measurements as plants grow
  • Update existing measurements if corrections are needed
  • Mark plants as deceased when applicable

This creates a clear historical record of each plant's development and survival, supporting long-term analysis of restoration outcomes.

Plot Observations

Monitoring plots also include an observations section for recording broader environmental changes within the plot.

Currently supported observations include:

  • Soil Moisture
  • Canopy Cover

Observations are recorded using a single, structured form and can be edited later if corrections are required. Additional observation types, such as bioacoustics, are planned for future updates.

Map View and Plot Visualization

Each monitoring plot includes a dedicated map view that shows:

  • The plot boundary
  • The location of plants within the plot

From this view, users can navigate to individual plant details and adjust plot dimensions when necessary. This spatial overview helps ensure accuracy and clarity during field monitoring.

Editing and Updating Plot Data

All monitoring plot data remains fully editable. Users can update plot details, plant records, observations, and locations to ensure data accuracy as monitoring progresses or new information becomes available.

Plot Groups

Monitoring plots can be organized into groups to simplify analysis and management.

  • A group can contain multiple monitoring plots
  • Each monitoring plot can belong to only one group

Groups are useful for organizing plots that share similar characteristics, objectives, or study designs, such as:

  • Control vs intervention comparisons
  • Long-term research areas
  • Specific restoration strategies

This structure helps users manage large monitoring efforts and analyze results across related plots.

What's Next?

After setting up your monitoring plot, you can: