Phenological changes are one of the most well recognised responses of organisms to climate change. The ability to detect phenological change often relies on long-term datasets, which are scarce in the global south. As the adaptive capacity of species is highly variable, it is important to improve our understanding of how species in southern hemisphere systems may be responding to climate change through shifts in their annual cycles. Citizen science projects, like bird Nest Record Schemes, offer valuable long-term data, although data quality can pose challenges, affecting their use in research. We investigated the suitability of the South African Nest Record Scheme for estimating lay dates and preliminary exploration of phenological shifts in four well-represented species. Firstly, this study explored the composition of nest records for each species, specifically the proportion of single- to multi-visit cards. Secondly, we explored the accuracy of single-visit cards in estimating lay dates compared to highly accurate multi-visit cards. Lastly, we compared analytical approaches to test for possible shifts in lay dates. For all species, a high proportion of records consisted of single-visits, however, our analysis suggested that both single- and multi-visit records mostly produced similar lay date estimates. This indicates that both single- and multi-visit records could be used for estimations of lay dates. Various analytical approaches were used to test whether different combinations of single- and multi-visit records exhibited the same trends. The different models showed a high degree of consistency in shifts of lay dates over time. However, a mixed model approach using all records, with card identity as a random term, was the most efficient and sensitive to assess shifts in lay dates. This study highlights the usefulness of the South African Nest Record Scheme in being able to detect phenological shifts in a region which is understudied in this regard.

We selected 6146 unique record cards from the period 1950-1999 for four common bird species (two passerines and two columbids) from the SANRS, with the most digitally available records at the time of this study. Details of the data and the sample sizes per species are summarised in Table 1. Nest record data were checked row by row for accuracy. Most records gave only a place name and region, so we assigned co-ordinates to each record using Google Earth and Google Maps search engines. Locations were assigned to the nearest plausible central point given the available information on each card. Records were excluded if they contained ambiguous information (missing dates, unclear type of breeding activity, unknown location) or were thought to be a repeat card of a previous nest record. For each species we calculated the start, peak and length of the egg-laying period for both single-visit and multi-visit records using the estimated lay dates. The start of egg-laying was defined as the 5th percentile of the distribution of all lay dates of a species, the peak of egg-laying as the median, and the length of egg-laying as the number of days between the 5th and 95th percentiles. We also calculated the proportion of multi-visit cards for each species. All statistical analyses were completed in R version 4.2.2.