Summary of Working Group Proceedings
Chair: Donat Agosti
Rapporteur: Chris Rodstrom
Background
Biodiversity conservation efforts focus primarily upon communities of organisms and the composition of these communities within a specific area. It is necessary, however, to place site-specific ecosystem monitoring within a broader global context, providing an overall understanding of how global conditions may be linked to biodiversity change at the local or regional level.
Data gathering and analysis of existing global-scale remotely-sensed data remain restricted to a relatively small group of scientists and researchers whose technical expertise allows them to manage the information. Global data sets currently made available by such organizations as NASA and the EPA tend to be very large and difficult to relate to smaller-scale regional observations at the community or species level.
In order to make these data accessible to the NGO/museum community, standardized data sets at a variety of levels of biological organization are needed. Additionally, organizations need to work with the biodiversity community in order to understand what kinds of information would be most useful in both the long- and short-run.
Central to this problem is how to go about collecting remote-sensing data on a global scale (e.g., concentrating on a specific feature such as forest cover) in a manner relevant for inference at the species level. By identifying needs and capabilities, the NGO/museum community can benefit from global scale monitoring by: comparing global scale data to detailed field data already held by conservation groups; superimposing NASA global scale maps on site data to locate patterns and changes; developing time series data sets to monitor how change may effect several species or habitats; and facilitating data sharing and increasing the amount of information available through the collection of various resolutions
Discussion of Issues
Current global vegetation maps tend to be too broad, allowing for the identification of various land classes yet insufficient for in-depth analysis of animal and plant distribution. The first task is then to identify what map elements conservation groups need for measuring and monitoring global biodiversity. For example, major interests for these groups include: population density, spatial fragmentation of habitat, and species movement. Global data sets are therefore necessary to locate what is occurring now in order to couple them with in situ data and higher resolution maps that can provide insight into species level change.
Measuring biodiversity and monitoring changes over the long-term will allow observation of changes in distribution. What must we focus upon? Perhaps species that are major components of larger systems, or those for which lots of data now exist. From there, a decision must be made between those who provide the data (NASA), and those who will utilize the data sets (NGO community), concerning the most effective short-term and long-term foci for collaborative research.
Parameters need to be defined for global models run at certain scales. The need to do so is urgent, as the International Geosphere Biosphere Programme (IGBP) is already building data sets. Because of the cost of providing global coverage, trade-offs may have to occur. One could measure at a broad, simplified global scale, or pinpoint specific areas/hot spots.
In situ data must in some way be tied to global remote-sensing data, e.g., global scale climate change could be linked to declines in amphibian populations. For this to occur, NASA must help make these data sets accessible to those who need them. It will be important to package such global information so data sets can be easily retrieved when researchers or NGOs request them.
How to Address the Issues
The group offered several specific suggestions:
- Concentrate effort on determining patterns of dominant features (extent of habitat for forests, etc.) and processes of observed changes in populations and habitats. Researchers need to explore what types of specific tools are needed in order to form and test hypotheses.
- For example, accumulate global data sets and climatic data that reveal how much desert, forest, etc., there is. Analyze those data together with site data to infer the potential range of species. Test the analytical framework by comparing specimen data from scattered, spatially-located sites.
- Focus especially on areas of rapid change. In order to detect change, areas of rapid population and habitat change must be monitored. Once these spots are identified, higher resolution data can be taken in order to accumulate specific measurements.
- Work with the IGBP researchers to include elements in their land-use history workshops that address biodiversity concerns.
- Remote sensing data are needed in areas for which biodiversity groups already have lots of data, or where major questions and concerns still exist. These include:
- Mata Atlantica forests -- have one of the highest number of tree species present in any studied forests
- Sulu Seas -- endangered, but hardly any data have been gathered
- World's coral reefs -- bleaching occurs, but we don't know why.
- In the long-term, temporal global maps could be collected. Smaller studies can be done in the short-term.
- Overall, 1-km maps already available should be layered with lower scale data of various kinds and, finally, high resolution data in order to achieve a fused data project. These fused data products should then be made available to outside users with a handbook/documentation of how analysis was done and what questions were answered in the process.
Recommended Pilot Project Characteristics
Organize a workshop for the development of a land-cover classification methodology reflecting habitat and structural data useful for the biodiversity community (to be included in IGBP study)
Construct a global distribution map for amphibian (frog) population, focusing on habitat make-up and biodiversity composition
Construct global data sets by region, working with detailed data already collected for specific sites. Coupling these data with NASA/NOAA 1-km maps would enable a calibration for larger areas
Collect time series data on global and regional scales
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