Managing Biodiversity Data
Biodiversity Monitoring Database
We have developed the BioMon, the Biodiversity Monitoring Database to help researchers using Biodiversity Monitoring Plots to manage and share their data in a consistent manner.
The Importance of Good Data Management
Good data management must be a component of any successful long-term forest biodiversity monitoring program. Over the past decade, there has been a sharp rise in the number of projects aimed at collecting temporal data about ecosystem dynamics, particularly projects that use permanent plots to monitor natural vegetative cycles over time. Long-term monitoring also provides a baseline for monitoring other taxonomic groups. Without standardized data management protocols, however, long-term monitoring will not be successful.
The importance of data management to long-term ecological research cannot be overstated. Without good data management, biodiversity monitoring information cannot be effectively interpreted or disseminated. In the past many researchers and others assumed that once data are collected they can be analyzed with ease. Consequently, organizations monitoring biodiversity provided inadequate personnel and funding for data management. Advancements in technology and methodologies, however, have enabled the collection of ever greater amounts of data, and researchers have come to recognize the crucial role of proper data management. Recent recommendations call for allocating as much as 20 to 25 percent of a monitoring program's budget to information management (Stohlgren et al. 1995).
Relational Databases
The most efficient way to manage biological information is with a relational database. Unfortunately, most researchers do not have a working knowledge of database management and are often limited to using spreadsheets (Stafford 1993). Designing such a database is a complex matter, but the payoff is high: users can dispense with tedious multiple entries, reducing the risk of error and saving time (Cooperrider et al. In press).
Relational databases contain linked tables, allowing users to access information that was entered elsewhere. For example, a master list of species is constructed to name each individual in the sample. The full name is entered only once, and all individuals of a species are linked with the same (relational) record describing that species. Most relational databases also contain a "look-up" table or "pick list" so that users can easily find a record in the master list.
In addition, relational databases allow users to manipulate data through a standardized database language called Structured Query Language (SQL). A powerful tool for analyzing biological data, SQL enables the manipulation of data and the retrieval of selected groups of records based on specific criteria. Other types of data management tools, such as spreadsheets, are less flexible.
Metadata
In recent years, significant attention has been focused on another area of data management—metadata standards. Metadata are the information that describes a database (Cooperrider et al. In press). Their primary purpose is to help users determine whether data in the database are of interest or will be useful, even when the original researcher or study manager cannot be contacted.
At a minimum, metadata should include the following information:
- location and purpose of the study
- data collected
- software used
- storage format and location
Currently, several large international agencies are developing guidelines for metadata standards. Should multiple standards be developed, however, comparison between different sites may not be possible. Software packages, such as Metamaker, are now available to assist researchers in maintaining metadata standards for their projects.
Quality Control
Quality control is the process of ensuring that data are generated within known and acceptable limits (Correll et al. In press). Data quality is known if it has been collected using accepted and documented protocols (Shampine 1993). This step is essential at every stage of biodiversity research and monitoring—from the collection of data in the field to the final analysis and publication of the information. Because many people are usually involved in the process of biodiversity monitoring, a predetermined level of accuracy should be agreed upon at each stage, especially concerning the treatment of data in the field. At no stage should accuracy be compromised; doing so will endanger the validity of the results.
Data Storage
Over time, all data become historical and cannot be collected again. Therefore, attention must be paid to proper preservation. Saving information derived from the data is not sufficient. The raw data must be safely stored to enable future analyses, not just comparisons with previous findings.
The normal tendency is to disperse data in the home institutions of the individuals conducting the research, a practice that makes it difficult for future researchers to make full use of the data. There are procedures to ease this burden. At the very least, copies of the data should be available in the field. In addition, electronic links can be established among storage locations and field stations. Many officially protected areas have on-site facilities that include room for storing research findings. In such cases, the area's data manager should be included as an integral part of the monitoring team to help ensure proper data handling and storage.
Recent efforts to improve user access to stored data include Access 1996, a project of the U.S. MAB program that lists all of the biosphere reserves in Europe and North America, the kinds of data that have been collected at each location, and the names of people to contact for more information. With the growing use of the Internet, much of this type of information is now available online.
MAB's Data Management Standardized Protocols
MAB has found that the use of consistent protocols for data management greatly enhances the effectiveness of biodiversity monitoring. The benefits are evident in the greater ease with which information from widely dispersed protected areas can be compared and shared and in the increased desire on the part of researchers to do so.
MAB has devised, tested, and carried out protocols for multi-taxa forest biodiversity monitoring for more than a decade. Our researchers use these standardized protocols at our nearly 300 monitoring plots, enabling them to integrate scientific research with analysis methods and get the results of their work into the hands of a wide range of users. Researchers and scientists at MAB work hard to ensure a rapid turn-around between the gathering of data in the field and the interpretation and publication of the data for use in additional research and on-the-ground management.
MAB's protocols include consistent conventions for collecting and managing huge amounts of data. Our objective is to provide a common currency that allows comparison among widely dispersed sites and facilitates the sharing of information. As part of this work we developed BioMon, a flexible biodiversity monitoring database for managing the information we collect from our global plot network.
In the future, we anticipate implementing a broader range of monitoring standards and associated data management tools for use in multi-taxa monitoring.
References
Comiskey, J. A., G. Ayzanoa, and F. Dallmeier. 1994. "A data management system for monitoring forest dynamics." Journal Tropical Forest Science 7(3): 419-27.
Comiskey, J. A., F. Dallmeier, G. Aymard, and A. Hanson. 1993. Biodiversity Survey of Kwakwani, Guyana. Smithsonian Institution/MAB Biodiversity Program, Washington, DC.
Cooperrider, A., L. Fox III, R. Garrett, and T. Hobbs. In press. "Data collection, management, and inventory." Ecological Stewardship: A Common Reference for Ecosystem Management. (N. Johnson, A. Malk, W. Sexton, and R. Szaro, eds). Island Press, Washington, DC.
Correll, C. S., C. A. Askren, R. Holmes, H. M. Lachowski, G. C. Panos, and W. B. Smith. In press. "Data management, collection, and inventory." Ecological Stewardship: A Common Reference for Ecosystem Management. (N. Johnson, A. Malk, W. Sexton, and R. Szaro, eds). Island Press, Washington, DC.
Dallmeier, F., R. B. Foster, C. Romano, R. Rice, and M. Kabel. 1991. A User's Guide to the Beni Biosphere Reserve Biodiversity Plots, 1. Smithsonian Institution, Washington, DC.
Shampine, W. J. 1993. "Quality assurance and quality control in monitoring programs." Environmental Monitoring and Assessment 26: 143-51.
Stafford, S. G. 1993. "Data, data everywhere but not a byte to read: managing monitoring information." Environmental Monitoring and Assessment 26: 125-41.
Stohlgren, T. J., D. Binkley, T. T. Veblen, and W. L. Baker. 1995. "Attributes of reliable long-term landscape-scale studies: malpractice insurance for landscape ecologists". Environmental Monitoring and Assessment 36: 1-25.
Wilson, D. E., and D. M. Reeder, eds. 1993. Mammal Species of the World: A Taxonomic and Geographic Reference. 2nd ed. Smithsonian Institution Press, Washington, DC.
