A webcam embedded among leaves.

Big Brother keeps its eye on leaves to measure the health of ecosystems

Phenocams, cameras that monitor leaf function, offer a promising new method to track and detect the impact of climate change on ecosystems, helping conservation efforts and ensuring long-term resilience.

Scientists from the PhenoCam Network have developed a powerful method for monitoring the resilience of ecosystems in the face of climate change. Using a network of phenocams—cameras that capture near-continuous observations of leaf function—they can detect changes in ecosystems as a result of severe weather events, stressful growing conditions, and other disturbances. This innovative approach, detailed in a paper published in Ecosphere by Spafford and colleagues, could help conservation managers better understand the impacts of climate change on ecological integrity.

Climate change is causing an increase in the frequency of severe weather events, such as hurricanes, windstorms, and frosts, as well as creating more stressful growing conditions for plants. These changes can impact the resilience of ecosystems, or their ecological integrity, which refers to the coherence of ecosystem processes like carbon and water cycling. Monitoring ecological integrity is crucial for conservation managers to ensure the long-term health of ecosystems in a changing world.

To test the effectiveness of phenocams in detecting ecological disturbances and stress, Spafford and colleagues examined 14 examples from the PhenoCam Network. These cases included a range of disturbances such as hurricanes, windstorms, frost, insect defoliation, and drought stress. The researchers found that frost and herbivory disturbances led to both reductions and extensions in the duration of the rising section of the greenness curve, while hurricanes generally resulted in reductions in the duration of the plateau section and entire leaf-on period.

The study established that changes of at least ±20% in the duration of the rising section of the seasonal greenness curve, ±20% in the duration of the plateau section following the seasonal greenness peak, and ±10% in the duration of the entire leaf-on period were reliable indicators of leaf functional declines due to disturbance or stress. These declines, if they become more frequent and severe due to climate change, could impact ecological integrity by disrupting ecosystem processes.

By comparing the duration of these periods in a given year to the average for other years using these thresholds, the researchers achieved an average true detection rate of 86% and a false-positive detection rate of 11%. This high accuracy demonstrates the potential of phenocams as efficient monitoring tools for ecological integrity.

The use of phenocams for monitoring ecological integrity offers a promising new approach for conservation managers to detect and track the impacts of climate change on ecosystems. In their article Spafford and colleagues write:

The application of the duration of periods from phenocam-derived greenness patterns as an ecological integrity indicator may be more complex than other traditional indicators in that it requires a nuanced consideration of a variety of factors, such as signal quality, species, and environment. Despite this complexity, the use of phenocams for ecological integrity monitoring provides several distinct advantages including automation, cost-efficiency, fine-scale sensitivity, and quantitative monitoring, with the potential for reduced complexity as new monitoring insights are developed. Other traditional methods for the monitoring of disturbance or stress effects such as aerial or field surveys require considerable time and financial resources for conservation managers. Phenocams also provide potential for ancillary research objectives with image time series including the dynamics of ice, snow, flowering, and other ecologically important phenomena in the scene (Jacobs et al., 2009). Understanding which species are robust, resilient, or susceptible to global change through the monitoring protocol we proposed here will provide insight for effective conservation and management activities (Chamberlain et al., 2019). 

Spafford et al. 2023

Spafford, L., MacDougall, A.H., Vitasse, Y., Filippa, G., Richardson, A., Steenberg, J. and Lever, J.J. (2023) “Leaf phenology as an indicator of ecological integrity,” Ecosphere (Washington, D.C), 14(5). Available at: https://doi.org/10.1002/ecs2.4487.

Dale Maylea

Dale Maylea was a system for adding value to press releases. Then he was a manual algorithm for blogging any papers that Alun Salt thinks are interesting. Now he's an AI-assisted pen name. The idea being telling people about an interesting paper NOW beats telling people about an interesting paper at some time in the future, when there's time to sit down and take things slowly. We use the pen name to keep track of what is being written and how. You can read more about our relationship with AI.

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