Digital Varroa Tracking: Dashboard and Forecasts

You diligently measure mite drop, keep records of your treatments, and try to stay on top of everything. But with 5, 10, or more colonies, it quickly becomes overwhelming: which colony had the high infestation again? Was the last treatment 3 or 4 weeks ago? Is the mite drop in the safe range?

In this lesson, we show you why digital Varroa tracking outperforms the paper card system, how to read infestation curves correctly, and how data-driven forecasts help you treat at the optimal time.

Why Track Digitally?

The Varroa mite cannot be assessed with a single glance. Its management is a process spanning the entire year, where trends, thresholds, and timing matter. This is exactly where analogue methods reach their limits.

The Limits of Paper Documentation

Reading and Interpreting Infestation Curves

The heart of digital Varroa tracking is the infestation curve: a chart showing the mite infestation over time. Once you learn to read this curve, you can identify problems early and act in a targeted manner.

The Typical Annual Infestation Curve

A healthy, well-treated colony shows this typical pattern:

January -- April (Rise Phase):

• Very low mite drop after winter treatment (below 0.5 mites/day)
• Slow increase as mites multiply with the growing brood
• No action needed yet

May -- June (Growth Phase):

• Stronger increase in mite drop
• The mite population grows exponentially (doubling every 3-4 weeks)
• Monitoring phase: regular checks every 3-4 weeks

July -- August (Critical Phase):

• Steep increase if untreated
• Thresholds are reached or exceeded
• Treatment must be running or start immediately

September -- November (Decline Phase):

• After successful treatment: clear decline in mite drop
• Slow decrease to low values
• Preparation for winter treatment

December (Reset):

• Winter treatment brings the infestation to near zero
• The cycle begins anew

Warning Signs in the Infestation Curve

Learn to recognise these warning signals:

Thresholds: When Does It Become Critical?

German bee institutes recommend the following thresholds for natural mite drop:

Mite Drop Forecasts: Predicting the Future

One of the greatest advantages of digital tracking is the ability to create forecasts. Based on the trend so far, the software can calculate when thresholds will likely be exceeded.

How Forecasts Work

The calculation is based on a simple yet powerful model:

1. Data basis: The last 3-4 mite drop measurements
2. Growth rate: The exponential mite reproduction is modelled (doubling every 3-4 weeks during the brood phase)
3. Seasonal adjustment: Temperature and brood development are factored in
4. Projection: The expected mite drop for the next 2-4 weeks is calculated

Example: Your colony shows a mite drop of 2 per day in early June. With a doubling rate of 3 weeks, the projected mite drop would be:

• End of June: approx. 4 mites/day
• Mid-July: approx. 8 mites/day
• End of July: approx. 16 mites/day -- well above the threshold

A forecast thus shows you already in early June: treatment needed by early to mid-July at the latest.

Limitations of Forecasts

Forecasts are estimates, not guarantees. The following factors can distort them:

• Reinvasion: Mites from collapsing neighbouring colonies can suddenly spike the infestation
• Swarming: A swarm takes many mites with it -- the infestation drops suddenly
• Weather: Cold spells or heat waves affect brood development and mite reproduction
• Nectar gaps: Brood breaks temporarily reduce mite reproduction

Therefore: forecasts are a valuable planning tool but do not replace regular measurement.

The Varroa Dashboard in Practice

A good Varroa dashboard shows you the status of all your colonies at a glance. Here are the key elements you need:

Status Overview of All Colonies

A traffic-light display immediately shows which colonies need attention:

• Green: Mite drop in the normal range, no action needed
• Yellow: Elevated mite drop, closer monitoring needed
• Red: Threshold exceeded, treatment needed

Infestation Trend per Colony

A line chart shows the mite drop over time -- ideally with marked thresholds and treatment dates. This lets you see at a glance:

• How the infestation has developed
• Whether the last treatment worked
• Whether the trend is heading in the right or wrong direction

Treatment History

Every treatment is captured with date, product, dosage, and result:

• Which product was used?
• How effective was it (mite drop before/after)?
• When is the next treatment due?

Automatic Alerts

The system actively warns you when:

• A threshold is exceeded
• The next monitoring measurement is due
• A treatment did not show the expected efficacy
• The forecast predicts a critical infestation

From Measurement to Decision

The real goal of tracking is not collecting data but making better decisions. Here is a typical decision flow:

1. Measure

   Insert monitoring board or perform powdered sugar test. Enter the mite drop value into the app.

2. Assess

   The dashboard shows you: is the value in the green, yellow, or red range? How has the value changed since the last measurement?

3. Check the Forecast

   When will the threshold likely be reached? Do you still have time, or must action be taken now?

4. Decide

   Based on measurement, trend, and forecast: continue monitoring? Prepare treatment? Treat immediately?

5. Act and Document

   Carry out the measure and record it in the system. Check efficacy at the next measurement.

Keeping Multiple Colonies in View

The more colonies you have, the more valuable digital tracking becomes. With 10+ colonies, keeping track without a system becomes nearly impossible.

Apiary Comparison

If you have colonies at different locations, the dashboard reveals differences:

• Does one apiary have generally higher mite infestation? (Possible cause: untreated colonies nearby)
• Do colonies at different apiaries respond differently to the same treatment?
• Are there location-specific factors (proximity to other beekeepers, reinvasion pressure)?

Using Historical Data

After 2-3 years of digital tracking, you have a valuable data treasure:

• Recognise annual patterns: In which month does the infestation typically become critical?
• Compare treatment success: Which method works best for your colonies?
• Support breeding decisions: Which colonies consistently show low mite infestation?

The Future: IoT and Automatic Monitoring

The next level of Varroa tracking will be enabled by IoT sensors (Internet of Things) on the beehive:

Hive scales can indirectly indicate Varroa:

• Unexpected weight loss can point to colony collapse due to Varroa
• Weight changes after treatment show the treatment's impact

Temperature sensors provide clues about the brood nest:

• Brood-free conditions in winter can be detected via the core temperature (below 35 °C = likely brood-free)
• The optimal timing for winter treatment becomes calculable

Acoustic sensors (in research):

• Certain frequency patterns may indicate elevated Varroa infestation
• Not yet field-ready, but a promising research direction

Knowledge Check

In the next and final lesson, we bring everything together: Integrated Varroa Management combines monitoring, biotechnical and chemical methods, and breeding progress into one comprehensive concept.