Background & Summary

Longitudinal data on individuals living in the wild represent the gold standard for research in organismal ecology, as subjects are sampled repeatedly over multiple stages of their life-history while being exposed to the natural evolutionary pressures of their native environments1. These types of data have offered evolutionary ecologists valuable insights into the selective processes that affect species over multiple generations such as, for example, the role of stochastic climate events shaping the beak morphologies of Darwin’s Finches2, the predator-prey cycles of mammal communities on the Serengeti3, or the demographic dynamics of alpine plants4 and animals5 in response to climate change. However, collecting field data over many consecutive years while following standardized methods requires substantial labour and consistent funding. Due to these challenges, raw longitudinal field data from wild populations are rarely made open to the public6 – thus limiting the transparency and reproducibility of published research methods and results in evolutionary ecology. Furthermore, releasing raw data has the potential benefit of stimulating more substantive discussion and criticism within the scientific community, which can advance research topics and forge productive collaborations. Here, we offer an open access database of our raw field observations over an 11-year period of 1,647 uniquely marked individuals from an important breeding population of snowy plovers (Charadrius nivosus) in Mexico.

Charadrius plovers are small ground-nesting shorebirds that occur worldwide. As a group, plovers present a model system for investigating fundamental and applied topics in organismal biology as they occupy open habitats that are easy to monitor and experimentally manipulate, and they exhibit intra- and interspecific variation in several behavioural, ecological, and demographic traits. For example, plovers display remarkable diversity and plasticity in breeding tactics with sex roles during courtship, mating, and parental care varying appreciably among populations both between and within species7. The snowy plover is native to North America8 and is one of the least abundant shorebirds on the continent (estimated population size: 25,869) with many populations in decline and requiring intensive management9. Apart from being a public icon of avian conservation, snowy plovers have also increasingly captured the spotlight for their intriguing ecology and life-history. Their unusual biology features a rare breeding behaviour characterized by highly dispersive polyandry and male-biased uniparental care10,11.

In this data descriptor we present CeutaOPEN – an open-access database containing the raw data from our fieldwork between 2006 and 2016 monitoring a breeding population of snowy plovers at Bahía de Ceuta, a subtropical lagoon on the coastal plain of north-western Mexico (23°54′N, 106°57′W). The database includes individual-based observations of reproductive effort, movements, morphometrics, and social behaviour (Fig. 1). Previously, we have used subsets of these data to report on a wide variety of topics in organismal biology, including sex ratio variation12, population viability13, courtship behaviour14, incubation behaviour15, parental care16, ontogeny17, chronobiology18, camouflage mechanisms19, offspring desertion20 and mating system dynamics21. The motivation for making our database open is to provide evolutionary ecologists with an accessible resource that will serve as an important repository for addressing overarching questions in organismal biology and conservation. Here we describe our field methods for collecting the observations presented in the database, we summarize the contents of the database, and we provide a code-based tutorial demonstrating how to import and query the database within the R environment and conduct, for example, a simple analytical workflow to investigate sex-specific ontogeny.

Fig. 1
figure 1

Schematic of the CeutaOPEN database. During fieldwork, data collection was divided across five main tasks: (a) nest monitoring, (b) captures of adults and chicks, (c) brood monitoring, (d) resightings of individually colour ringed adults, and (e) determining the identity of all breeding pairs and their offspring. The data obtained during each of these activities are structured in our database as the five tables shown here that contain a common variable such as a nest “ID” or a bird “code”, that can be utilized by the user for relational queries.


Study area

Plovers breeding in Bahía de Ceuta mainly concentrate their activities on 200 ha of salt flats that contain several abandoned evaporation ponds. This habitat (hereafter “salina”) is surrounded by red mangrove (Rhizophora mangle) and characterized by sparse vegetation and open substrates. Nesting typically commences in late March or early April when flooding from spring tides and high precipitation recedes. By mid-July the breeding season concludes when rains and spring tides resubmerge the salina. Throughout the remainder of the year, the flooded salina and surrounding lagoons are used as important wintering habitats for plovers and other migratory shorebirds, with the region being protected by the Ramsar convention22. Our monitoring effort throughout the 11-year study period was focused on the largest contiguous section of salt flats in the study area where the vast majority of known breeding activity occured (Fig. 2a,b). However, in drought years or at the peak of the breeding season when tidewaters had maximally retreated, we made observations of plovers nesting and tending broods in several small pockets of salina adjacent to the main study site (Fig. 2a).

Fig. 2
figure 2

(a) Map of the Bahía de Ceuta study site and photos of the (b) salina breeding habitat and (c) a mobile hide in which observers conduct non-invasive field work.

Data collection

Over the 11-year study period, we monitored the population daily between April and July, and once every month or two during the remainder of the year. We used a car and mobile hides23 (Fig. 2c) to search for nests, broods, and determine the identity of breeding plovers with binoculars and scopes. During fieldwork, our data collection was divided across four main field tasks: (1) nest monitoring, (2) captures of adults and chicks, (3) brood monitoring, and (4) resights of individually colour ringed adults. The data obtained during each of these activities are structured in our database as tables (Fig. 1) containing a common variable such as a nest “ID” or a bird “code”, that can be utilized by the user for relational queries. The basic format of these tables was taken from ref. 24. Fieldwork permits to collect the data presented in CeutaOPEN were granted by the Secretaría de Medio Ambiente y Recursos Naturales (SEMARNAT). All of our field activities were performed in accordance with the approved ethical guidelines outlined by SEMARNAT. Here we explain the details of our data collection pertinent to the database.

Nest data

We regularly searched for nests (Fig. 1a) and incubating plovers by traversing the salina on foot, by car or in a mobile hide19 (Fig. 2c). Upon discovery, we recorded the nest’s geographic location, the found date and time, and measured the width and length of each egg in the clutch with calipers. To estimate the initiation-date of the clutch (i.e., date when the first egg was laid), we floated each egg in a jar of water and scored the embryonic stage of development according to a calibrated table25. For hatched clutches that were initially discovered more than 10 days after laying, we estimated initiation-date by subtracting 25 days (i.e., the mean incubation time in our population18) from the hatching date and subtracting an additional 5 days to account for a 2-day egg laying interval11. We checked nests every 2–7 days to assess survival and identify tending parents.

Capture data

We captured plover chicks by hand and adults using mist nets or funnel traps on broods or nests. To individually identify members of the population, we assigned adults a unique combination of three to four colour leg rings and an alpha-numeric metal ring (see photo in Fig. 1d). Likewise, we marked chicks less than 2 weeks old with a single colour ring and a metal ring (see photo in Fig. 1c). Given our intensive nest search and capture efforts, we are confident that we ringed the vast majority of chicks (>95%) and breeding adults (>85%) in the local breeding population every year. During captures, we sampled the metatarsal vein of chicks or the brachial vein of adults and drew 25–50 μL of blood for subsequent genetic analyses. Additionally, we measured body mass, bill length, tarsus length, and wing length for all captured individuals (Fig. 3). As snowy plovers exhibit only minor sexual dimorphisim in plumage and body size, we molecularly determined sex using the Z-002B marker26 and verification with the Calex-31 marker located on the W chromosome27 for all adults and chicks captured before 2014. For PCR conditions see ref. 17.

Fig. 3
figure 3

Schematic of an example analytical workflow using CeutaOPEN within the R environment to investigate how chick morphometric data may be used to study growth and ontogeny. (a) Import the database into R using the RSQLite31 package. (b) Use the dplyr32 package to join the ‘Captures’ table with the ‘Nests’ table by nest “ID” to determine the “hatch_date” of each captured individual. Subset the result to individuals that have repeated captures and calculate the “age” at capture by subtracting the “hatch_date” by the capture “date”. (c) Use the bamlss33 package (i.e., “Bayesian Additive Models for Location, Scale, and Shape”) to determine the sex-specific growth trends while controlling for repeated measures within individuals and random annual variation. Plot the fitted values to visualise the trends (see Supplementary File 1 for more details).

Brood data

Similar to our data collection of nests, we resighted broods (see photo in Fig. 1c) every 1–7 days to assess chick survival and determine sex-specific patterns of parental care and desertion. Each brood observation includes the time, distance and azimuth from the observer to the brood, geographic location of the observer, number of chicks seen, and the identity of them and their parents.

Resight data

We typically resighted colour ringed individuals (see photo in Fig. 1d) opportunistically while in the field. Since 2009 we surveyed the entire salina within a single day at least once during the breeding season to record all colour ringed individuals present. As with our brood data, each resight includes the distance and azimuth to the individual, the geographic location of the observer, and any noteworthy comments pertaining to the individual’s behaviour.

Data Records

Our database and all other files described in this manuscript are stored in a publicly available OSF repository28. The file Ceuta_OPEN_vX-X.sqlite contains the SQL (Structured Query Language) database of four tables containing our raw observations collected during routine fieldwork (Nests, Captures, Broods, and Resights), and a fifth table (BirdRef) that uses relational information to summarize the identities of the parents and offspring belonging to each nest and subsequent brood. The structure of these tables is defined in Tables 15 below. This Data Descriptor is based on version 1.4 of the CeutaOPEN database.

Table 1 Nests data of snowy plovers breeding in Bahía de Ceuta, Mexico, between 2006 and 2016.
Table 2 Captures data of snowy plovers breeding in Bahía de Ceuta, Mexico, between 2006 and 2016.
Table 3 Broods data of snowy plovers breeding in Bahía de Ceuta, Mexico, between 2006 and 2016.
Table 4 Resights data of snowy plovers breeding in Bahía de Ceuta, Mexico, between 2006 and 2016.
Table 5 Bird Reference (“BirdRef”) data of snowy plovers breeding in Bahía de Ceuta, Mexico, between 2006 and 2016.

In summary, the CeutaOPEN database contains information on 794 surveyed nests, 2,824 captures of 1,647 marked individuals, 415 monitored broods, and 6,939 resightings of colour-marked individuals. Over the 11-year study period, we spent 927 days collecting these data in the field – amounting to over 20,000 hours of observational effort.

CeutaOPEN is one of only a few open-access databases to provide raw field observations of an individually-marked wild vertebrate species (for other examples, see refs. 29,30). We therefore believe our database will provide a valuable model for future field biologists to consult when structuring their data and deciding whether to provide public access.

Technical Validation

During each field season of the snowy plover project at Bahía de Ceuta, observers receive comprehensive training on our sampling protocol25 and general avian field methodology. In all 11 years of data collection, at least one of us was present in the field to oversee fieldwork and assess the quality of observations. Moreover, field assistants usually aided us with fieldwork for academic purposes (e.g., as part of a bachelor, master, or doctoral project), which encouraged personal interest in maximizing the quality of their data collection. All breeding data from the 2014 breeding season was lost, which is why this year is missing the nest and brood data (Table 6). Likewise, 2015 does not include brood data because broods were not resighted in this year (Table 6).

Table 6 Annual summary in data of captures conducted, nests surveyed, broods monitored, and resights of colour-marked individuals.

During the data processing and development of the final database, verification and validations were made at several stages: during fieldwork we would regularly check each other’s notes for unusual observations, during the digitization of field data in spreadsheets we would scrutinize outlier measurements, and throughout the assembly of the SQL database we conducted thorough data cleaning (e.g., removing white space from strings, enforcing consistent notation and symbology, etc.). These data quality checks were run annually before merging new observations with the master database.

Usage Notes

The CeutaOPEN database is available under a Creative Commons Attribution 4.0 International Public License, whereby anyone may freely use and adapt our data, as long as the original source is credited, the original license is linked, and any changes to our data are indicated in subsequent use. The database has undergone multiple rounds of curation to purge inconsistencies and errors. Any further errors that are spotted by us or brought to our attention by users will be corrected and documented in future version releases of the database. When using any of the CeutaOPEN materials presented here, please cite this Data Descriptor in addition to the version of the database that was used. Furthermore, for all projects making considerable use of the CeutaOPEN database, we encourage users to reach out to us to offer the opportunity to comment prior to the publication of their work.

We recommend that users employ R to access and wrangle the CeutaOPEN database for their study. To help this process, please refer to the accompanying RMarkdown document (Supplementary File 1) to follow our suggested analytical workflow for utilizing CetuaOPEN with the RSQLite31 and dplyr32 packages in the R environment.