Agriculture covers ~38% of the world’s land area and over 50% of the US. Such a large land-use, combined with growing populations, creates an urgent need for more productive agriculture that protects and promotes environmental integrity. The USDA’s Long-Term Agroecosystem Research Network (LTAR) aims to fulfill this need by simultaneously enhancing agriculture’s productivity, minimizing its environmental footprint, and promoting rural prosperity.
LTAR comprises 18 locations across the US, representing row crops, grazinglands, and integrated systems. LTAR complements other ecological networks by representing diverse agroecosystems conducting stakeholder-driven science. LTAR sites are within 12 NEON ecoclimatic domains and use both experimental and observational approaches that capitalize on historic data records. LTAR’s hallmark common experiment contrasts site-specific “business as usual” management and “aspirational” management strategies for sustainably intensifying production, while assessing tradeoffs among ecosystem services, and using common indicators to understand and model outcomes.
LTAR is exploring ways to integrate with other ecological networks. Multiple networks overlap in ecological data generation, but data accessibility and integration of vast amounts of data challenge network science. Here we share lessons-learned from LTAR which may inform challenges to cross-network collaboration as well as some early success stories of data integration across networks.
Results/Conclusions
To address data accessibility, LTAR is investing in data inventory, cataloging, automation, standardization, and integration. Data flows into multiple data repositories, websites and portals, and modeling tools. An open data hub (AgCROS) integrates diverse, networked data.
An LTAR analysis of water budgets tackled the issue of integrating datasets of variable length and collected using diverse methods by calculating uncertainty estimates for each water budget component, based on these two factors. The analysis compared water budget components across the network and identified further monitoring needs for understanding agricultural productivity and environmental impacts.
Early successes of cross-network integration include utilizing common measurements across networks. An analysis of 14 NEON and 5 LTAR sites used data from modified-Whittaker plots to understand how plant diversity in grazinglands may mediate the response of productivity to precipitation and management intensity. Another study used phenocams to quantify the relationship between phenological metrics and productivity across 16 LTAR, 1 LTER, and 2 NEON sites to refine productivity models.
LTAR fills existing gaps in networked science by including diverse agroecosystems and integrating stakeholder needs into its science initiatives. Increased collaboration and interoperability with other network data systems will create opportunities for cross-network synergies and broad-scale synthesis.