From 1937 - 1958 Belgian scientists stationed at the Yangambi Research Station in the Democratic Republic of the Congo observed key tree life cycle events, e.g. fruit development, flowering and leaf shedding of more than 2000 trees.
In an effort to bring these old observations, which only exist on paper, into the 21th century and preserve the original copy we digitized the life cycle summary tables.
The Jungle Rhythms project was started to ensure the preservation and transcriptions of the digitized hand-drawn observations of the life cycle events. These historical long term observations are an extraordinary source of botanical information and key to understanding the future of tropical forests in a changing world.
Jungle Rhythms strives to transcribe old observations of tree life cycle events (flowering, leaf shedding, fruit dispersion), which are key to understanding a tree's functioning. The African rainforest, the second largest on Earth, covers ~630 million ha and stores up to 66 Pg of carbon. It is presently a persistent carbon sink, offsetting large amounts of human CO2 emissions. Drought events in tropical rainforests have the potential to alter forest structure. However, due to data scarcity, little is known on how droughts affect the structure and function of African rainforests. In this project we will try to link long term observations of tree life cycle events with weather data. This will allow us to track the trees' responses to variation in rainfall and temperature. This data may provide us with key information on how sensitive tree species are to drought, and how this sensitivity might alter the structure and function of the forest as drought regimes change.
Our current understanding of life cycle events of plants relies largly on consistent long term observations of these events. These long-term observations have regularly been collected in temperate regions (outside the tropics). Most of these observations have been collected by enthusiast naturalists and researchers as well as citizen scientists.
However, observing life cycle events of tropical trees is particularly difficult. The dense impenetrable nature of tropical forests, as well as their remote location, makes observing the life cycle of these trees very challenging, even for the most dedicated scientists. Yet, gathering and interpreting the life cycle events of tropical trees is key to understanding the future of tropical forests in a changing world.
From 1937-1958 scientists stationed at the Yangambi research station in the Democratic Republic of the Congo made an effort to observe more than 2,000 trees on a weekly basis, writing down key life cycle events, e.g. fruit development, flowering and leaf shedding. All of these weekly observations were jotted down in little notebooks and finally summarized in large hand-drawn tables. In an effort to recover the key parts of this knowledge, which currently only exists on paper, and preserve the original copy, Jungle Rhythms will transcribe the summary tables. In addition, these unique data will tell us how tropical forests respond to changing patterns in temperature and rain. As such, the data will allow us to predict the future state of the forest using historical data.
The nature of the notation used, mainly using fine hand-drawn pencil lines overlaying another fine gray line, make it really hard to process these images automatically. The human eye and brain is finely tuned to finding patterns and picking up these slight nuances in shading. Participants also have background knowledge of the project, and this contextual information further helps in understanding the notes. Participants are presented with yearly sections and are be asked to annotated features within the section. At the end of the project annotations will be combined into a timeline of each trees' life cycle events and matched with weather data.
All we currently know is that these observations were made by research scientists at the Yangambi agricultural research station between 1937 - 1958. During our efforts to digitize the data, we did not come across any mention of names associated with project. The age of the data set would also make it very unlikely that observers are still alive today. We do know that some of the observations were made along the roads in and around Yangambi, as we found evidence of maps referencing the number associated with each specimen. We assume that a fair amount of the observations were made in a research forest nearby. It also remains a mystery why the observations were made. As the research station was focused on agriculture and forestry, we assume that the researchers at the time might have wanted to understand the life cycle events of a trees better in order to optimize forestry practices.
As participants work on Jungle Rhythms, we will try to trace some of the data's historic context. Looking through archives might not only provide context, but also additional data. We already posses the climate data as measured at the research station, which is key to understanding the life cycle events. We know that a similar dataset was collected at the botanical research forest in Luki on the Atlantic side of DR Congo. The two forests differ significantly in weather patterns. The existence of coordinated observations confirms that this was a deliberate experimental design, so we believe a motivation and clear description of the methods used should have been documented.
All original data exists in the public domain. To encourage future research and the free distribution of scientific data all data will be available under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license upon completion of the project.
Project Lead, Ecologist
Citizen Science Specialist, Ecologist
(Université de Kisangani)
This project was made possible with support of the Belgian Science Policy Office (Congo Basin integrated monitoring for forest carbon mitigation and biodiversity; contract no. SD/AR/01A), Institut National pour l’Etude et la Recherche Agronomiques (INERA) YGB and the National Science Foundation’s Macro-system Biology Program (award EF-1065029).