Modeling plant phenology database: Blending near-surface remote phenology with on-the-ground observations

Abstract

Phenology research handles multifaceted information that needs to be organized and made promptly accessed by scientific community. We propose the conceptual design and implementation of a database to store, manage, and manipulate phenological time series and associated ecological information and environmental data. The database was developed in the context of the e-phenology project and integrates ground-based conventional plant phenology direct observations with near-surface remote phenology using repeated images from digital cameras. It also includes site-base information, sensor derived data from the study site weather station and plant ecological traits (e.g., pollination and dispersal syndrome, flower and fruit color, and leaf exchange strategy) at individual and species level. We validated the database design through the implementation of a Web application that generates the time series based on queries, exemplified in two case studies investigating: the relationship between flowering phenology and local weather; and the consistency between leafing patterns derived from ground-based phenology on leaf flush and from vegetation image indices (%Green). The database will store all the information produced in the e-phenology project, monitoring of 12 sites from cerrado savanna to rainforest, and will aggregate the legacy information of other studies developed in the Phenology Laboratory (UNESP, Rio Claro, Brazil) over the last 20 years. We demonstrate that our database is a powerful tool that can be widely used to manage complex temporal datasets, integrating legacy and live phenological information from diverse sources (e.g., conventional, digital cameras, seed traps) and temporal scales, improving our capability of producing scientific and applied information on tropical phenology.

Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis

“…Phenology data are periodically collected from individuals located in an observation area named site and the data values of observation vary according to the sampling method used by experts (Morellato et al, 2010b). In our research, we use data collected in the context of the long term Cerrado Phenology (Camargo et al, 2011) and the multidisciplinary e-phenology project (Mariano et al, 2016b;Alberton et al, 2014Alberton et al, , 2017.…”

“…Basically, the data managed in the context of the e-phenology project can be classified into two types: (i) non-temporal and (ii) temporal data. These data are stored into conventional databases (Mariano et al, 2016b). Non-temporal data are related to species taxonomy, location, and ecological information about species and individuals.…”

“…Common research questions addressed in those studies refer to the analysis of numerical data related, for example, to when (time of the year), for how long (duration), and at which intensity a given event (e.g., leafing or flowering) has occurred at a specific region (Talora and Morellato, 2000;Morellato et al, 2010b). The most typical approach to store conventional numerical data associated with phenology studies relies on the use of relational databases (Mariano et al, 2016b;Dierenbach et al, 2013).…”

“…A common approach used for data organization relies on the use of database-oriented solutions, such as relational databases, to store plant phenology data (Dierenbach et al, 2013;Mariano et al, 2016b). Despite their success, the need of visual analytics tools still persists.…”

“…The objective is to support the detection of cyclical patterns. We demonstrate the potential use of our tool in the context of phenology studies using data from the e-phenology project as a case study (Alberton et al, 2014;Mariano et al, 2016b).…”