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Seeds provide the basis of genetic diversity in perennial grassland communities and their traits may influence ecosystem resistance to extreme drought. However, we know little about how drought effects the community functional composition of seed traits and the corresponding implications for ecosystem resistance to drought.

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In terrestrial ecosystems, climate change forecasts of increased frequencies and magnitudes of wet and dry precipitation anomalies are expected to shift precipitation–net primary productivity (PPT–NPP) relationships from linear to nonlinear. Less understood, however, is how future changes in the duration of PPT anomalies will alter PPT–NPP relationships. A review of the literature shows strong potential for the duration of wet and dry PPT anomalies to impact NPP and to interact with the magnitude of anomalies. Within semi‐arid and mesic grassland ecosystems, PPT gradient experiments indicate that short‐duration (1 year) PPT anomalies are often insufficient to drive nonlinear aboveground NPP responses. But long‐term studies, within desert to forest ecosystems, demonstrate how multi‐year PPT anomalies may result in increasing impacts on NPP through time, and thus alter PPT–NPP relationships. We present a conceptual model detailing how NPP responses to PPT anomalies may amplify with the duration of an event, how responses may vary in xeric vs. mesic ecosystems, and how these differences are most likely due to demographic mechanisms. Experiments that can unravel the independent and interactive impacts of the magnitude and duration of wet and dry PPT anomalies are needed, with multi‐site long‐term PPT gradient experiments particularly well‐suited for this task.

To cope with uncertainty and variability in their environment, plants evolve distinct life‐history strategies by allocating different fractions of energy to growth, survival and fecundity. These differences in life‐history strategies could potentially influence ecosystem‐level dynamics, such as the sensitivity of primary production to resource fluctuations. However, linkages between evolutionary and ecosystem dynamics are not well understood.

In semiarid regions, vegetation constraints on plant growth responses to precipitation (PPT) are hypothesized to place an upper limit on net primary productivity (NPP), leading to predictions of future shifts from currently defined linear to saturatingNPP–PPTrelationships as increases in both dry and wetPPTextremes occur. We experimentally tested this prediction by imposing a replicated gradient of growing seasonPPT(GSP,n = 11 levels,n = 4 replicates), ranging from the driest to wettest conditions in the 75‐yr climate record, within a semiarid grassland. We focused on responses of two key ecosystem processes: abovegroundNPP(ANPP) and soil respiration (R_s).ANPPandR_sboth exhibited greater relative responses to wet vs. dryGSPextremes, with a linear relationship consistently best explaining the response of both processes toGSP. However, this responsiveness toGSPpeaked at moderate levels of extremity for both processes, and declined at the most extremeGSPlevels, suggesting that greater sensitivity ofANPPandR_sto wet vs. dry conditions may diminish under increased magnitudes ofGSPextremes. Underlying these responses was rapid plant compositional change driven by increased forb production and cover asGSPtransitioned to extreme wet conditions. This compositional shift increased the magnitude ofANPPresponses to wetGSPextremes, as well as the slope and variability explained in theANPP–GSPrelationship. Our findings suggest that rapid plant compositional change may act as a mediator of semiarid ecosystem responses to predicted changes inGSPextremes.

Ongoing intensification of the hydrological cycle is altering rainfall regimes by increasing the frequency of extreme wet and dry years and the size of individual rainfall events. Despite long‐standing recognition of the importance of precipitation amount and variability for most terrestrial ecosystem processes, we lack understanding of their interactive effects on ecosystem functioning. We quantified this interaction in native grassland by experimentally eliminating temporal variability in growing season rainfall over a wide range of precipitation amounts, from extreme wet to dry conditions. We contrasted the rain use efficiency (RUE) of above‐ground net primary productivity (ANPP) under conditions of experimentally reduced versus naturally high rainfall variability using a 32‐year precipitation–ANPP dataset from the same site as our experiment. We found that increased growing season rainfall variability can reduce RUE and thus ecosystem functioning by as much as 42% during dry years, but that such impacts weaken as years become wetter. During low precipitation years, RUE is lowest when rainfall event sizes are relatively large, and when a larger proportion of total rainfall is derived from large events. Thus, a shift towards precipitation regimes dominated by fewer but larger rainfall events, already documented over much of the globe, can be expected to reduce the functioning of mesic ecosystems primarily during drought, when ecosystem processes are already compromised by low water availability.

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building.