The kelpforest database (http://kelpforest.ucsc.edu/) is an online tool we developed to provide a means for expediting the process by which information is accumulated, organized, and made accessible to those making and using ecological network models specific to temperate kelp forests. For more information check out this peer reviewed article for more details.
This project started with funding from an NSF/NOAA CAMEO program. Our group of collaborators at the USGS, PISCO, and NOAA are making spatial and temporal comparisons of the empirical structure and dynamics of central and southern California nearshore kelp forest communities to inform and compare the performance of multi-species approaches to understanding the complex dynamics of these systems. To inform these analysis and parameterize models, the construction of this database was needed.
We started with literature searches of the most common species in kelp forests ecosystems. But we quickly realized that kelp forests were more complex and diverse than we thought. As of today, we have identified more than 800 different species associated with these ecosystems and more than 3600 different interactions between this species.
All the natural history traits, demographics and species interaction information is spatially and temporally explicit in the database. For example, the database is capable of store information of where and when an interaction occur in California. To do this, we have developed an interactive map split in three different scales:
We have been working on informing this database for over three years. Despite our efforts and time invested in this project, there is a lot more information out there that we need to include in this tool. We see this project as a growing open source, open science community effort.
We have used this database to inform some ecosystem models already. We used them to explore how fishing, climate change and the predation of a keystone species effects on species interactions of these systems.
We encourage ecosystem modelers, other scientist and general public to use this database to better understand one of the most productive coastal marine ecosystems in the world.