The FLUXNET2015 dataset provides ecosystem-scale data on CO₂, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Novel cellular behaviors and characteristics can be obtained by coupling engineered gene networks to the cell's natural regulatory circuitry through appropriately designed input and output interfaces. Here, we demonstrate how an engineered genetic circuit can be used to construct cells that respond to biological signals in a predetermined and programmable fashion. We employ a modular design strategy to create Escherichia coli strains where a genetic toggle switch is interfaced with: ( i ) the SOS signaling pathway responding to DNA damage, and ( ii ) a transgenic quorum sensing signaling pathway from Vibrio fischeri. The genetic toggle switch endows these strains with binary response dynamics and an epigenetic inheritance that supports a persistent phenotypic alteration in response to transient signals. These features are exploited to engineer cells that form biofilms in response to DNA-damaging agents and cells that activate protein synthesis when the cell population reaches a critical density. Our work represents a step toward the development of “plug-and-play” genetic circuitry that can be used to create cells with programmable behaviors.

Leaf seasonality in Amazon forests: Models assume that lower precipitation in tropical forests means less plant-available water and less photosynthesis. Direct measurements in the Amazon, however, show that production remains constant or increases in the dry season. To investigate this mismatch, Wu et al. use tower-based cameras to detect the phenology (i.e., the seasonal patterns) of leaf dynamics in tropical tree crowns in Amazonia, Brazil, and relate this to patterns of CO ₂ flux. Accounting for age-dependent variation among individual leaves and crowns is necessary for understanding the seasonal dynamics of photosynthesis in the entire ecosystem. Leaf phenology regulates seasonality of the carbon flux in tropical forests across a gradient of climate zones. Science , this issue p. 972

The leaf economics spectrum^1,2 and the global spectrum of plant forms and functions³ revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species². Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities⁴. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability^4,5. Here we derive a set of ecosystem functions⁶ from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems^7,8.