Using Essential Biodiversity Variables (EBVs) As a Framework for Coordination Between Research and Monitoring Networks: A Case Study with Phenology

Friday, 19 December 2014
Katherine D. Jones1, Jesslyn F Brown2, Sarah Elmendorf1, Carolyn Enquist3, Alyssa Rosemartin3, Andrea Thorpe1, Brian Wee1 and Jake F Weltzin3, (1)NEON Inc., Boulder, CO, United States, (2)USGS/EROS, Sioux Falls, SD, United States, (3)USA National Phenology Network, Tucson, AZ, United States
The United Nations Convention on Biological Diversity (CBD) was organized to encourage countries to take action to address issues of declining biodiversity. In2010, the CBD identified specific goals for 2011-2020 (the “Aichi Targets”) and a tiered system of indicators necessary to achieve those targets. Essential biodiversity variables (EBVs) are the standardized measurements and observations at the base of this system; they are the basic level of information that is necessary to calculate these indicators. By providing a list of pre-defined EBVs, existing research and research planned for the future can align measurements to address common questions.

We assessed the applicability of phenology EBVs for standardizing measurements across observation networks within the US as a test case for use of the standardized used of EBVs. Phenology products from the USA National Phenology Network, a citizen science observer based program, NEON, a multi-scale ecological observatory, and remotely sensed data from USGS EROS were considered for this purpose.

Essential Biodiversity Variables currently defined for phenology are insufficient to support consistent measurement across monitoring networks. Specifically, phenology which is a field of study, is currently listed as a single EBV within the general category of ‘species traits’. With the only guidance provided to future observation networks being that of measuring ‘phenology,’ there would likely be as many approaches to achieving this goal as networks participating. We propose more narrowly defined variables which may be more appropriate for standardization and demonstrate how these measurements satisfy the basic characteristics of an EBV in that they are relevant, sensitive to change, biological and generalizable, scalable, feasible, stable and, represent state variables. We map these variables to the tiered indicators identified by the CBD and, finally, to Aichi Targets to which they contribute.

EBVs may be used not only to align measurements from different research projects but also to facilitate coordination between projects working at different scales; our framework provides a model that may be applied at a global scale.