Robust estimates of biodiversity change require high-resolution time series

Area of Science:

• Ecology
• Environmental Science
• Biodiversity Research

Background:

• Accurate biodiversity change estimates are crucial for conservation and management.
• Temporal data limitations can compromise the reliability of biodiversity trend analysis.
• Understanding the influence of temporal resolution is key to improving monitoring strategies.

Purpose of the Study:

• To investigate how temporal resolution (sampling frequency and duration) affects estimates of river invertebrate biodiversity trends.
• To compare biodiversity trend directions and magnitudes derived from simulated and real-world datasets with varying temporal resolutions.
• To determine the sensitivity of biodiversity trend direction versus magnitude to temporal data resolution.

Main Methods:

• Utilized 1,353 European river invertebrate time series (≥ 10 years).
• Simulated reduced sampling frequencies (2-6 years) and durations (2-9 years).
• Compared trends from reduced resolution data against complete time series; analyzed two real-world datasets with differing resolutions.

Main Results:

• Reducing sampling frequency (2-6 years) resulted in 73-87% match in trend direction but only 39-78% match in magnitude.
• Reducing duration (2-9 years) led to 52-88% direction match and 8-86% magnitude match.
• Real-world data comparison showed 53% direction match but only 12% magnitude match between datasets of different resolutions.

Conclusions:

• Biodiversity change magnitude is more sensitive to temporal resolution than trend direction.
• High-resolution time series are necessary for accurate estimates of both biodiversity trend direction and magnitude.
• Lower-resolution data may be useful for indicating trend direction but is insufficient for precise magnitude assessment.