The circular nature of recurrent life cycle events: a test comparing tropical and temperate phenology

Abstract

The high diversity of plant species in the tropics has revealed complex phenological patterns and reproductive strategies occurring throughout the year. Describing and analysing tropical plant phenology, and detecting triggers, demands to consider the circular nature of recurrent life cycle events and the use of appropriated statistical metrics. Here, we explore analytical pitfalls potentially affecting results of studies that do not consider the circular nature of phenology data when comparing resting and non‐resting systems, especially when accounting for phylogeny. We discuss definitions of the widely used first flowering date and revisit the literature on phylogenetic signal in plant phenology. We compare statistical analyses for tropical and temperate phenology by simulating communities with known phenological and phylogenetic structures. We demonstrate that ignoring the circular nature of phenological data underestimates the phylogenetic signal in plant phenology. Using the proposed circular transformation for non‐resting tropical ecosystems and resting temperate systems prevented errors, yielding precise comparisons. Synthesis. The analysis of both non‐resting and resting systems must consider the circularity of phenological events. Circular statistics is the appropriate approach to calculate phenological parameters, identify phylogenetic signal and assess drivers, allowing accurate cross‐comparisons of phenology across environments at large spatial scales.

Vegetative and reproductive phenology in a tropical grassland–savanna–forest gradient

“…10 individuals multiplied by the value 4) and then multiplied by 100. The period of manifestation of the seasonal phenophases of each species of campo rupestre , cerrado and forest were characterized using circular statistical analysis (Morellato et al, 2010; Staggemeier et al, 2020). The peak intensity of a phenophase was determined as the month with the highest intensity index recorded for each of the phenophases.…”

“…A circular distribution was used with the frequency of species showing the peak intensity of the phenophases in each month. This was done by converting months into angles and, given that a circle is 360°, the months were defined by 30° intervals, with January corresponding to 15°, February to 45° and so on (Fisher, 1995; Staggemeier et al, 2020).…”

“…Both metrics were calculated using the R package picante (Kembel et al, 2010). Due to the circular nature of the phenological data, the mean angle of the phenological peak of each species was linearized through species ordination based on a matrix of angular distances between species (principal coordinates analysis [PCoA]; Staggemeier et al, 2020). When the first phenological vector explained more than 70% of the variation in phenology, the second vector was not evaluated, assuming that the first vector is sufficient to explain the position of species in the phenological space.…”

“…Both metrics were calculated using the R package picante (Kembel et al, 2010). Due to the circular nature of the phenological data, the mean angle of the phenological peak of each species was linearized through species ordination based on a matrix of angular distances between species (principal coordinates analysis [PCoA]; Staggemeier et al, 2020).…”

Between locality variations in the seasonal patterns of dung beetles: the role of phenology in mitigating global warming effects

“…Circular statistics and graphs were used to estimate and visualise the seasonal patterns of each one of the selected species in the studied localities (Staggemeier et al, 2020) using the Oriana v.4 software (Kovach, 2011). To do that, the numbers of individuals of each species collected in each study site and survey period were standardised considering the total of individuals of each species.…”