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Abstract The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, R S ), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and R S are irreconcilable. When we estimate GPP based on R S measurements and some assumptions about R S :GPP ratios, we found the resulted global GPP values (bootstrap mean $${149}_{-23}^{+29}$$ 149 − 23 + 29 Pg C yr −1 ) are significantly higher than most GPP estimates reported in the literature ( $${113}_{-18}^{+18}$$ 113 − 18 + 18 Pg C yr −1 ). Similarly, historical GPP estimates imply a soil respiration flux (Rs GPP , bootstrap mean of $${68}_{-8}^{+10}$$ 68 − 8 + 10 Pg C yr −1 ) statistically inconsistent with most published R S values ( $${87}_{-8}^{+9}$$ 87 − 8 + 9 Pg C yr −1 ), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global R S :GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget. 

Abstract The conversion of native ecosystems to residential ecosystems dominated by lawns has been a prevailing land‐use change in the United States over the past 70 years. Similar development patterns and management of residential ecosystems cause many characteristics of residential ecosystems to be more similar to each other across broad continental gradients than that of former native ecosystems. For instance, similar lawn management by irrigation and fertilizer applications has the potential to influence soil carbon (C) and nitrogen (N) pools and processes. We evaluated the mean and variability of total soil C and N stocks, potential net N mineralization and nitrification, soil nitrite (NO₂⁻)/nitrate (NO₃⁻) and ammonium (NH₄⁺) pools, microbial biomass C and N content, microbial respiration, bulk density, soil pH, and moisture content in residential lawns and native ecosystems in six metropolitan areas across a broad climatic gradient in the United States: Baltimore, MD (BAL); Boston, MA (BOS); Los Angeles, CA (LAX); Miami, FL (MIA); Minneapolis–St. Paul, MN (MSP); and Phoenix, AZ (PHX). We observed evidence of higher N cycling in lawn soils, including significant increases in soil NO₂⁻/NO₃⁻, microbial N pools, and potential net nitrification, and significant decreases in NH₄⁺pools. Self‐reported yard fertilizer application in the previous year was linked with increased NO₂⁻/ NO₃⁻content and decreases in total soil N and C content. Self‐reported irrigation in the previous year was associated with decreases in potential net mineralization and potential net nitrification and with increases in bulk density and pH. Residential topsoil had higher total soil C than native topsoil, and microbial biomass C was markedly higher in residential topsoil in the two driest cities (LAX and PHX). Coefficients of variation for most biogeochemical metrics were higher in native soils than in residential soils across all cities, suggesting that residential development homogenizes soil properties and processes at the continental scale. 

Abstract In urban areas, anthropogenic drivers of ecosystem structure and function are thought to predominate over larger‐scale biophysical drivers. Residential yards are influenced by individual homeowner preferences and actions, and these factors are hypothesized to converge yard structure across broad scales. We examined soil total C and total δ¹³C, organic C and organic δ¹³C, total N, and δ¹⁵N in residential yards and corresponding reference ecosystems in six cities across the United States that span major climates and ecological biomes (Baltimore, Maryland; Boston, Massachusetts; Los Angeles, California; Miami, Florida; Minneapolis‐St. Paul, Minnesota; and Phoenix, Arizona). Across the cities, we found soil C and N concentrations and soil δ¹⁵N were less variable in residential yards compared to reference sites supporting the hypothesis that soil C, N, and δ¹⁵N converge across these cities. Increases in organic soil C, soil N, and soil δ¹⁵N across urban, suburban, and rural residential yards in several cities supported the hypothesis that soils responded similarly to altered resource inputs across cities, contributing to convergence of soil C and N in yards compared to natural systems. Soil C and N dynamics in residential yards showed evidence of increasing C and N inputs to urban soils or dampened decomposition rates over time that are influenced by climate and/or housing age across the cities. In the warmest cities (Los Angeles, Miami, Phoenix), greater organic soil C and higher soil δ¹³C in yards compared to reference sites reflected the greater proportion of C₄plants in these yards. In the two warm arid cities (Los Angeles, Phoenix), total soil δ¹³C increased and organic soil δ¹³C decreased with increasing home age indicating greater inorganic C in the yards around newer homes. In general, soil organic C and δ¹³C, soil N, and soil δ¹⁵N increased with increasing home age suggesting increased soil C and N cycling rates and associated¹²C and¹⁴N losses over time control yard soil C and N dynamics. This study provides evidence that conversion of native reference ecosystems to residential areas results in convergence of soil C and N at a continental scale. The mechanisms underlying these effects are complex and vary spatially and temporally. 

Abstract During the 21st century, human–environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human–environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi‐resolution information for analysis. Climate change, land‐use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high‐density, and high‐resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) for Socio‐Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross‐site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio‐environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data.