Scaling NEON biological data from points to the continent

Background/Question/Methods

The NEON framework provides the scientific community with an unprecedented opportunity, and an unprecedented challenge, to scale biological data from points to the continent. We tested multi-scale vegetation plots in the Central Plains Experiment Station (core area for the Central Plains Domain) to assess the scalability of invasive plant species data.  One preliminary question we asked was whether the ratio of non-native to native plant species was consistent and predictable across spatial scales.

Results/Conclusions

We stratified vegetation types based on the National Land Cover Data, and used a standard multi-scale plot method consisting of a 7.3-m radius plot, with three nested 1-m² subplots in summer, 2008. We compared data to county-level species data provided by the Biota of North America Program (www.BONAP.org). Preliminary analysis demonstrated that the percentages of non-native plant species (of total plant species) is fairly consistent across spatial scales, varying from 7.7% (±1.3%) at 1-m2 scales (n=60 subplots) to 9.6% (±2.0%) at 168-m2 scales (n=20 plots), and 10% to 15% at county-level scales throughout the domain. Mesic vegetation types in the core area contained predictably higher non-native species richness in comparison to xeric vegetation types. This pattern transcended scales across the domain, where 24 xeric counties averaged 10.0%  (±0.6%) non-native species in comparison to 18 mesic counties that averaged 14.4%  (±0.5%) and for the conterminous U.S.  This is one small step in scaling biological data across scales.  Additional efforts are underway to evaluate the scalability of data from small mammal traps and pitfall traps. Cost-efficiency is a primary concern for sampling.  We are testing a sample optimization scheme to help select a small number of potential NEON sample sites throughout the domain with respect to current environmental variation (precipitation, temperature, EVI, solar radiation, and elevation), future environmental variation (thirty-year projected changes in precipitation and temperature, and land use change), and cost relative to core sampling areas.  This generalized approach may be useful for conservation agencies and non-government organizations in designing long-term monitoring programs for harmful invasive species and native biodiversity in the wake of climate change and land use change.  We welcome the scientific community to get involved to help create a National Ecological Observatory Network.