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Summary It has been 60 years since the discovery of C₄photosynthesis, an event that rewrote our understanding of plant adaptation, ecosystem responses to global change, and global food security. Despite six decades of research, one aspect of C₄photosynthesis that remains poorly understood is how the pathway fits into the broader context of adaptive trait spectra, which form our modern view of functional trait ecology. The C₄CO₂‐concentrating mechanism supports a general C₄plant phenotype capable of fast growth and high resource‐use efficiencies. The fast‐efficient C₄phenotype has the potential to operate at high productivity rates, while allowing for less biomass allocation to root production and nutrient acquisition, thereby providing opportunities for the evolution of novel trait covariances and the exploitation of new ecological niches. We propose the placement of the C₄fast‐efficient phenotype near the acquisitive pole of the world‐wide leaf economic spectrum, but with a pathway‐specific span of trait space, wherein selection shapes both acquisitive and conservative adaptive strategies. A trait‐based perspective of C₄photosynthesis will open new paths to crop improvement, global biogeochemical modeling, the management of invasive species, and the restoration of disturbed ecosystems, particularly in grasslands. 

Variability of the terrestrial global carbon sink is largely determined by the response of dryland productivity to annual precipitation. Despite extensive disturbance in drylands, how disturbance alters productivity-precipitation relationships remains poorly understood. Using remote-sensing to pair more than 5600 km of natural gas pipeline corridors with neighboring undisturbed areas in North American drylands, we found that disturbance reduced average annual production 6 to 29% and caused up to a fivefold increase in the sensitivity of net primary productivity (NPP) to interannual variation in precipitation. Disturbance impacts were larger and longer-lasting at locations with higher precipitation (>450 mm mean annual precipitation). Disturbance effects on NPP dynamics were mostly explained by shifts from woody to herbaceous vegetation. Severe disturbance will amplify effects of increasing precipitation variability on NPP in drylands. 

Summary Microbial nitrogen (N) fixation accounts forc. 97% of natural N inputs to terrestrial ecosystems. These microbes can be free‐living in the soil and leaf litter (asymbiotic) or in symbiosis with plants. Warming is expected to increase N‐fixation rates because warmer temperatures favor the growth and activity of N‐fixing microbes.We investigated the effects of warming on asymbiotic components of N fixation at a field warming experiment in Puerto Rico. We analyzed the function and composition of bacterial communities from surface soil and leaf litter samples.Warming significantly increased asymbiotic N‐fixation rates in soil by 55% (to 0.002 kg ha⁻¹ yr⁻¹) and by 525% in leaf litter (to 14.518 kg ha⁻¹ yr⁻¹). This increase in N fixation was associated with changes in the N‐fixing bacterial community composition and soil nutrients.Our findings suggest that warming increases the natural N inputs from the atmosphere into this tropical forest due to changes in microbial function and composition, especially in the leaf litter. Given the importance of leaf litter in nutrient cycling, future research should investigate other aspects of N cycles in the leaf litter under warming conditions. 

Abstract Background and AimsTropical forests exchange more carbon dioxide (CO2) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three times greater for the tropics than other for ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink. MethodsWe used a meta-analytic approach, focusing on tropical photosynthetic temperature responses, to address this knowledge gap. Our dataset, gleaned from 18 independent studies, included leaf-level light-saturated photosynthetic (Asat) temperature responses from 108 woody species, with additional temperature parameters (35 species) and rates (250 species) of both maximum rates of electron transport (Jmax) and Rubisco carboxylation (Vcmax). We investigated how these parameters responded to mean annual temperature (MAT), temperature variability, aridity and elevation, as well as also how responses differed among successional strategy, leaf habit and light environment. Key ResultsOptimum temperatures for Asat (ToptA) and Jmax (ToptJ) increased with MAT but not for Vcmax (ToptV). Although photosynthetic rates were higher for ‘light’ than ‘shaded’ leaves, light conditions did not generate differences in temperature response parameters. ToptA did not differ with successional strategy, but early successional species had ~4 °C wider thermal niches than mid/late species. Semi-deciduous species had ~1 °C higher ToptA than broadleaf evergreen species. Most global modelling efforts consider all tropical forests as a single ‘broadleaf evergreen’ functional type, but our data show that tropical species with different leaf habits display distinct temperature responses that should be included in modelling efforts. ConclusionsThis novel research will inform modelling efforts to quantify tropical ecosystem carbon cycling and provide more accurate representations of how these key ecosystems will respond to altered temperature patterns in the face of climate warming. 

Abstract Decomposition is the transformation of dead organic matter into its inorganic constituents. In most biomes, decomposition rates can be accurately predicted with simple mathematical models, but these models have long under‐predicted decomposition in globally extensive drylands.We posit that the exposed surface conditions characteristic of drylands make litter decomposition uniquely subject to microsite‐specific environmental controls and spatially variable microbial communities. As such, decomposition in dryland ecosystems—which are characterized by extremes in temporal heterogeneity of climate conditions and spatial heterogeneity of vegetation cover with corresponding microclimate variability—is a prime example of a macrosystems process that can be addressed by merging field data with new predictive process models operating across a hierarchical continuum of spatial scales and process resolutions.A macrosystems approach offers promise to reconcile model‐measurement discrepancies by integrating observations and experiments across multiple scales, from microsites (e.g. shrub sub‐canopy or intercanopy) to regions (e.g. across a 100s of km²study site with complex topography, precipitation and temperature) and ultimately to a continental perspective (e.g. North American drylands).Recent developments in technology and data availability position the scientific community to integrate laboratory, field, modelling and remote sensing approaches across a hierarchical range of scales to capture the spatiotemporal distribution of litter and environmental conditions needed to predict decay dynamics at the micro‐to‐macroscale. This multi‐scale approach promises a path forward to resolving a longstanding disconnect between measured data and modelled processes in dryland litter decomposition.Dryland litter decomposition presents an excellent case study for resolving spatially and temporally complex biogeochemical dynamics through a hierarchical, multidisciplinary macrosystems approach.We focus on dryland litter decomposition, but the hierarchical, multidisciplinary macrosystems approach we outline shows great potential for resolving other spatially and temporally complex biogeochemical processes across a wide range of ecosystems. Read the freePlain Language Summaryfor this article on the Journal blog.