Environmental OSM: what can trees tell us about climate change?

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Environmental OSM is an attempt to provide OpenStreetMap tools to help tackle global warming, sustainable development and biodiversity. OpenStreetMap is proving to be an invaluable tool for a wide variety of projects and industries throughout the world and it also has the potential to help many environmental projects.

Objective

We are hopeful that our “prototype survey” may be a useful example for further “OSM-based” and “DWC/GBIF-compatible” tree data collections.

Background information

Scientists at the National Weather Service have been keeping track of weather in the United States since 1891. But trees can keep a much longer record of Earth’s climate. In fact, trees can live for hundreds — and sometimes even thousands — of years![1] Trees are important because as the biggest plants on the planet, they give us oxygen, store carbon, stabilize the soil and give life to the world’s wildlife. They also provide us with the materials for tools and shelter. Not only are trees essential for life, but as the longest living species on earth, they give us a link between the past, present and future.[2] Because trees are sensitive to local climate conditions, such as rain and temperature, they give scientists some information about that area’s local climate in the past. For example, tree rings usually grow wider in warm, wet years and they are thinner in years when it is cold and dry. If the tree has experienced stressful conditions, such as a drought, the tree might hardly grow at all in those years.

One way that scientists use trees to learn about past climate is by studying a tree’s rings. A tree's growth rate changes in a predictable pattern throughout the year in response to seasonal climate changes, resulting in visible growth rings.

Critical to the science, trees from the same region tend to develop the same patterns of ring widths for a given period of historical study. These patterns can be compared and matched ring for ring with trees growing at the same time in the same geographical zone and therefore under similar climatic conditions. When these tree-ring patterns are carried back, from tree to tree in the same locale, chronologies (tree-ring history) can be built up for entire geographical regions. A tree-ring history whose beginning and end dates are not known can be anchored by cross-matching a section against another chronology whose dates are known. A fully anchored and cross-matched oak and pine chronology in central Europe extends back 12,460 years.[3]

Official biodiversity data repositories indexed by GBIF

The Global Biodiversity Information Facility (GBIF) is an international open data infrastructure, funded by governments. It allows anyone, anywhere to access data about all types of life on Earth, shared across national boundaries via the Internet. By encouraging and helping institutions to publish data according to common standards, GBIF enables research not possible before, and informs better decisions to conserve and sustainably use the biological resources of the planet.[4]

Community-based data contributions

Scientific tree inventory data helps both, environmental institutions and communities, to create plans for forest management, environmental conservation and climate change adaption. Citizen Science based data collections are expected to increase public participation in citizen science research, broaden understanding of the natural world, and provide the foundation for meaningful contributions that advance scientific discovery, particularly for the growing number of research projects that require data input across multiple geographic and temporal extents.

There is a definite need for collecting and storing tree data, more specifically, tree plots that have been observed by citizens: students, average adventurer, or even foresters. In Los Angeles, the Earthwatch Institute trains rains volunteers to identify trees and collect data to understand how urban trees grow and provide cooling benefits across the LA basin. The data they collect will be used by scientists at the University of California to determine the water usage and cooling benefits of common urban tree species in Los Angeles.[5]

A recent PLOSONE publication compare community members and trained scientists data on tree diversity in permanent vegetation plots in montane forest in Yunnan, China. They show that local community members can collect tree diversity data of comparable quality to trained botanists. The community monitors received 1–2 days’ training from an intermediate organization (research institution) on how to establish plots and measure tree girth, as required for assessing the above-ground biomass.[6]

Potential data sources

This lists Darvin-core standardized OpenStreetMap data which is compatible with GBIF.

Following the above cited objectives of Environmental OSM we promote the integration of highly valuable community data like OSM and contributors with official data form. Our examples are superlative trees, already broadly registered and described in scientific literature, environmental institutions and communities, e.g. in:

  1. https://en.wikipedia.org/wiki/List_of_superlative_trees
  2. http://www.monumentaltrees.com/en/
  3. http://www.gbif.org/
  4. http://eol.org/

Results

Our biological occurrences are represented by ordinary OMS-nodes (POI-data) like node 4637447918, and as such, all registers and nodes can be found and explored inside OSM, applying e.g. Taginfo and Overpass turbo queries like:

try it yourself in overpass-turbo
[out:json][timeout:25];
// gather results
(
  // query part for: “"dwc:scientificName"=*”
  node["dwc:scientificName"];
  way["dwc:scientificName"];
  relation["dwc:scientificName"];
);
// print results
out body;
>;
out skel qt;

and

try it yourself in overpass-turbo
[out:json][timeout:25];
// gather results
(
  // query part for: “"dwc:scientificName"="Fitzroya cupressoides"”
  node["dwc:scientificName"="Fitzroya cupressoides"];
  way["dwc:scientificName"="Fitzroya cupressoides"];
  relation["dwc:scientificName"="Fitzroya cupressoides"];
);
// print results
out body;
>;
out skel qt;

or exported as “raw data” to the CSV-based DWC-A-format[7] supported, among many others, by GBIF an EOL. You can run the queries above by clicking at the steering wheel.

References