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Drought is often thought to reduce ecosystem photosynthesis. However, theory suggests there is potential for increased photosynthesis during meteorological drought, especially in energy-limited ecosystems. Here, we examine the response of photosynthesis (gross primary productivity, GPP) to meteorological drought across the water-energy limitation spectrum. We find a consistent increase in eddy covariance GPP during spring drought in energy-limited ecosystems (83% of the energy-limited sites). Half of spring GPP sensitivity to precipitation was predicted solely from the wetness index (R² = 0.47,p < 0.001), with weaker relationships in summer and fall. Our results suggest GPP increases during spring drought for 55% of vegetated Northern Hemisphere lands ( >30° N). We then compare these results to terrestrial biosphere model outputs and remote sensing products. In contrast to trends detected in eddy covariance data, model mean GPP always declined under spring precipitation deficits after controlling for air temperature and light availability. While remote sensing products captured the observed negative spring GPP sensitivity in energy-limited ecosystems, terrestrial biosphere models proved insufficiently sensitive to spring precipitation deficits.

 

ABSTRACT Seismic waves can couple with the atmosphere and generate sound waves. The influence of faulting mechanisms on earthquake sound patterns provides opportunities for earthquake source characterization. Sound radiated from earthquakes can be perceived as disturbing, even at low ground-shaking levels, which can negatively impact the social acceptance of geoengineering applications. Motivated by consistent reports of felt and heard disturbances associated with the weeks-long stimulation of a 6-km-deep geothermal system in 2018 below the Otaniemi district of Espoo, Helsinki, we conduct fully coupled 3D numerical simulations of wave propagation in the solid Earth and the atmosphere. We assess the sensitivity of the ground shaking and audible noise distributions to the source geometry of the induced earthquakes based on the properties of the largest local magnitude ML 1.8 event. Utilizing recent computational advances and the open-source software SeisSol, we model seismoacoustic frequencies up to 25 Hz, thereby reaching the lower limit of the human audible sound frequency range. We present synthetic distributions of shaking and audible sounds at the 50–100 m scale across a 12 km × 12 km area and discuss implications for better understanding seismic nuisances in metropolitan regions. In five 3D coupled elastic–acoustic scenario simulations that include data on topography and subsurface structure, we analyze the ground velocity and pressure levels of earthquake-generated seismic and acoustic waves. We show that S waves generate the strongest sound disturbance with sound pressure levels ≤0.04 Pa. We use statistical analysis to compare our noise distributions with commonly used empirical relationships. We find that our 3D synthetic amplitudes are generally smaller than the empirical predictions and that the interaction of the source mechanism-specific radiation pattern and topography can lead to significant nonlinear effects. Our study highlights the complexity and information content of spatially variable audible effects associated with small induced earthquakes on local scales. 

Abstract We present H -band (1.65 μ m) and SOFIA HAWC+ 154 μ m polarization observations of the low-mass core L483. Our H -band observations reveal a magnetic field that is overwhelmingly in the E–W direction, which is approximately parallel to the bipolar outflow that is observed in scattered IR light and in single-dish 12 CO observations. From our 154 μ m data, we infer a ∼45° twist in the magnetic field within the inner 5″ (1000 au) of L483. We compare these new observations with published single-dish 350 μ m polarimetry and find that the 10,000 au scale H -band data match the smaller-scale 350 μ m data, indicating that the collapse of L483 is magnetically regulated on these larger scales. We also present high-resolution 1.3 mm Atacama Large Millimeter/submillimeter Array data of L483 that reveals it is a close binary star with a separation of 34 au. The plane of the binary of L483 is observed to be approximately parallel to the twisted field in the inner 1000 au. Comparing this result to the ∼1000 au protostellar envelope, we find that the envelope is roughly perpendicular to the 1000 au HAWC+ field. Using the data presented, we speculate that L483 initially formed as a wide binary and the companion star migrated to its current position, causing an extreme shift in angular momentum thereby producing the twisted magnetic field morphology observed. More observations are needed to further test this scenario. 

Abstract. Evaporation (E) and transpiration (T) respond differentlyto ongoing changes in climate, atmospheric composition, and land use. It isdifficult to partition ecosystem-scale evapotranspiration (ET) measurementsinto E and T, which makes it difficult to validate satellite data and landsurface models. Here, we review current progress in partitioning E and T andprovide a prospectus for how to improve theory and observations goingforward. Recent advancements in analytical techniques create newopportunities for partitioning E and T at the ecosystem scale, but theirassumptions have yet to be fully tested. For example, many approaches topartition E and T rely on the notion that plant canopy conductance andecosystem water use efficiency exhibit optimal responses to atmosphericvapor pressure deficit (D). We use observations from 240 eddy covariance fluxtowers to demonstrate that optimal ecosystem response to D is a reasonableassumption, in agreement with recent studies, but more analysis is necessaryto determine the conditions for which this assumption holds. Anothercritical assumption for many partitioning approaches is that ET can beapproximated as T during ideal transpiring conditions, which has beenchallenged by observational studies. We demonstrate that T can exceed 95 %of ET from certain ecosystems, but other ecosystems do not appear to reachthis value, which suggests that this assumption is ecosystem-dependent withimplications for partitioning. It is important to further improve approachesfor partitioning E and T, yet few multi-method comparisons have beenundertaken to date. Advances in our understanding of carbon–water couplingat the stomatal, leaf, and canopy level open new perspectives on how toquantify T via its strong coupling with photosynthesis. Photosynthesis can beconstrained at the ecosystem and global scales with emerging data sourcesincluding solar-induced fluorescence, carbonyl sulfide flux measurements,thermography, and more. Such comparisons would improve our mechanisticunderstanding of ecosystem water fluxes and provide the observationsnecessary to validate remote sensing algorithms and land surface models tounderstand the changing global water cycle. 

Abstract The leaf economics spectrum 1,2 and the global spectrum of plant forms and functions 3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species 2 . Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities 4 . 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 functions 6 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 .