Effects of sampling methodology on phenology indices: insights from sites across India and modelling

Abstract

Plant phenology is the study of timing and extent of leaf, flower, and fruit production. Phenology data are used to study drivers of cyclicity and seasonality of plant life-history stages, interactions with organisms such as pollinators, and effects of global change factors. Indices such as timing of phenological events, proportion of individuals in a particular phenophase, seasonality, and synchrony have often been used to summarise plant phenology data. However, these indices have specific utilities and limitations and may be sensitive to sampling methodology, making cross-site comparisons challenging, particularly when data collection methods vary in terms of sample size, observation frequency, and the resolution at which phenophase intensity scores/values are recorded. We use fruiting phenology data from tropical trees across five sites in India to study the effects of sampling methodology on two indices: an index of population-level synchrony (overlap), and an index of seasonality. We supplement these results with simulations of fast- and slow-changing phenologies to test for the effects of sampling methodology on these indices. We found that the overlap index is sensitive to the phenophase intensity measurement resolution--with coarser intensity measures leading to overestimation of the overlap index. The seasonality index, on the other hand, was not affected by intensity resolution. Simulations indicated that finer intensity resolution is more important than frequency of observation to accurately estimate population synchrony and seasonality for fast- and slow-changing phenophases. Based on our findings, we provide recommendations for study design of future tropical tree phenology research, particularly for long-term or cross-site studies.

Plant phenotyping relevance

植物のフェノロジー指標について、観察頻度・サンプルサイズ・フェノフェーズ強度の測定解像度が指標推定に与える影響を実データとシミュレーションで検証しており、表現型データ取得・解析方法が中心である。

Code and data availability

The paper uses fruiting phenology data from four Indian field sites and SeasonWatch citizen science data, plus simulations, but no supplied block contains an authors' public data or code deposit with an actionable URL. The SeasonWatch dataset is cited as a reference without a public authors' URL, and no code or data-av

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