Water availability is the major limiting factor of the functioning of deserts and grasslands and is going to be severely modified by climate change. Field manipulative experiments of precipitation represent the best way to explore cause-effect relationships between water availability and ecosystem functioning. However, there is a limited number of that type of studies because of logistic and cost limitations. Here, we report on a new system that alters precipitation for experimental plots from 80% reduction to 80% increase relative to ambient, that is low cost, and is fully solar powered. This two-part system consists of a rainout shelter that intercepts water and sends it to a temporary storage tank, from where a solar-powered pump then sends the water to sprinklers located in opposite corners of an irrigated plot. We tested this automated system for 5 levels of rainfall, reduction-irrigation (50–80%) and controls with N = 3. The system showed high reduction/irrigation accuracy and small effect on temperature and photosynthetically active radiation. System average cost was $228 USD per module of 2.5 m by 2.5 m and required low maintenance.

We present a case for using Global Community Innovation Platforms (GCIPs), an approach to improve innovation and knowledge exchange in international scientific communities through a common and open online infrastructure. We highlight the value of GCIPs by focusing on recent efforts targeting the ecological sciences, where GCIPs are of high relevance given the urgent need for interdisciplinary, geographical, and cross-sector collaboration to cope with growing challenges to the environment as well as the scientific community itself. Amidst the emergence of new international institutions, organizations, and meetings, GCIPs provide a stable international infrastructure for rapid and long-term coordination that can be accessed by any individual. This accessibility can be especially important for researchers early in their careers. Recent examples of early-career GCIPs complement an array of existing options for early-career scientists to improve skill sets, increase academic and social impact, and broaden career opportunities. We provide a number of examples of existing early-career initiatives that incorporate elements from the GCIPs approach, and highlight an in-depth case study from the ecological sciences: the International Network of Next-Generation Ecologists (INNGE), initiated in 2010 with support from the International Association for Ecology and 20 member institutions from six continents.

Advances in the acquisition and dissemination of knowledge over the last decade have dramatically reshaped the way that ecological research is conducted. The advent of large, technology-based resources such as iNaturalist, Genbank, or the Global Biodiversity Information Facility (GBIF) allow ecologists to work at spatio-temporal scales previously unimaginable. This has generated a new approach in ecological research: one that relies on large datasets and rapid synthesis for theory testing and development, and findings that provide specific recommendations to policymakers and managers. This new approach has been termed action ecology, and here we aim to expand on earlier definitions to delineate its characteristics so as to distinguish it from related subfields in applied ecology and ecological management. Our new, more nuanced definition describes action ecology as ecological research that is (1) explicitly motivated by the need for immediate insights into current, pressing problems, (2) collaborative and transdisciplinary, incorporating sociological in addition to ecological considerations throughout all steps of the research, (3) technology-mediated, innovative, and aggregative (i.e., reliant on ‘big data'), and (4) designed and disseminated with the intention to inform policy and management. We provide tangible examples of existing work in the domain of action ecology, and offer suggestions for its implementation and future growth, with explicit recommendations for individuals, research institutions, and ecological societies.

Climate change will result in increased precipitation variability with more extreme events reflected in more frequent droughts as well as more frequent extremely wet conditions. The increase in precipitation variability will occur at different temporal scales from intra to inter-annual and even longer scales. At the intra-annual scale, extreme precipitation events will be interspersed with prolonged periods in between events. At the inter-annual scale, dry years or multi-year droughts will be combined with wet years or multi-year wet conditions. Consequences of this aspect of climate change for the functioning ecosystems and their ability to provide ecosystem services have been underexplored. We used a process-based ecosystem model to simulate water losses and soil-water availability at 35 grassland locations in the central US under 4 levels of precipitation variability (control, +25, +50 + 75 %) and six temporal scales ranging from intra- to multi-annual variability.

We show that the scale of temporal variability had a larger effect on soil-water availability than the magnitude of variability, and that inter- and multi-annual variability had much larger effects than intra-annual variability. Further, the effect of precipitation variability was modulated by mean annual precipitation. Arid-semiarid locations receiving less than about 380 mm yr^-1 mean annual precipitation showed increases in water availability as a result of enhanced precipitation variability while more mesic locations (>380 mm yr^-1) showed a decrease in soil water availability. The beneficial effects of enhanced variability in arid-semiarid regions resulted from a deepening of the soil-water availability profile and a reduction in bare soil evaporation. The deepening of the soil-water availability profile resulting from increase precipitation variability may promote future shifts in species composition and dominance to deeper-rooted woody plants for ecosystems that are susceptible to state changes. The break point, which has a mean of 380-mm with a range between 440 and 350 mm, is remarkably similar to the 370-mm threshold of the inverse texture hypothesis, below which coarse-texture soils had higher productivity than fine-textured soils.