Consistent time allocation fraction to vegetation green-up versus senescence across northern ecosystems despite recent climate change.

Extended growing season lengths under climatic warming suggest increased time for plant growth. However, research has focused on climatic impacts to the timing or duration of distinct phenological events. Comparatively little is known about impacts to the relative time allocation to distinct phenological events, for example, the proportion of time dedicated to leaf growth versus senescence. We use multiple satellite and ground-based observations to show that, despite recent climate change during 2001 to 2020, the ratio of time allocated to vegetation green-up over senescence has remained stable [1.27 (± 0.92)] across more than 83% of northern ecosystems. This stability is independent of changes in growing season lengths and is caused by widespread positive relationships among vegetation phenological events; longer vegetation green-up results in longer vegetation senescence. These empirical observations were also partly reproduced by 13 dynamic global vegetation models. Our work demonstrates an intrinsic biotic control to vegetation phenology that could explain the timing of vegetation senescence under climate change.

Extreme drought impacts have been underestimated in grasslands and shrublands globally.

Climate change is increasing the frequency and severity of short-term (~1 y) drought events-the most common duration of drought-globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function-aboveground net primary production (ANPP)-was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

Timing and magnitude of drought impacts on carbon uptake across a grassland biome.

Although drought is known to negatively impact grassland functioning, the timing and magnitude of these impacts within a growing season remain unresolved. Previous small-scale assessments indicate grasslands may only respond to drought during narrow periods within a year; however, large-scale assessments are now needed to uncover the general patterns and determinants of this timing. We combined remote sensing datasets of gross primary productivity and weather to assess the timing and magnitude of grassland responses to drought at 5 km2 temporal resolution across two expansive ecoregions of the western US Great Plains biome: the C4 -dominated shortgrass steppe and the C3 -dominated northern mixed prairies. Across over 700,000 pixel-year combinations covering more than 600,000 km2 , we studied how the driest years between 2003-2020 altered the daily and bi-weekly dynamics of grassland carbon (C) uptake. Reductions to C uptake intensified into the early summer during drought and peaked in mid- and late June in both ecoregions. Stimulation of spring C uptake during drought was small and insufficient to compensate for losses during summer. Thus, total grassland C uptake was consistently reduced by drought across both ecoregions; however, reductions were twice as large across the more southern and warmer shortgrass steppe. Across the biome, increased summer vapor pressure deficit (VPD) was strongly linked to peak reductions in vegetation greenness during drought. Rising VPD will likely exacerbate reductions in C uptake during drought across the western US Great Plains, with these reductions greatest during the warmest months and in the warmest locations. High spatiotemporal resolution analyses of grassland response to drought over large areas provide both generalizable insights and new opportunities for basic and applied ecosystem science in these water-limited ecoregions amid climate change.

Traits that distinguish dominant species across aridity gradients differ from those that respond to soil moisture.

Many plant traits respond to changes in water availability and might be useful for understanding ecosystem properties such as net primary production (NPP). This is especially evident in grasslands where NPP is water-limited and primarily determined by the traits of dominant species. We measured root and shoot morphology, leaf hydraulic traits, and NPP of four dominant North American prairie grasses in response to four levels of soil moisture in a greenhouse experiment. We expected that traits of species from drier regions would be more responsive to reduced water availability and that this would make these species more resistant to low soil moisture than species from wetter regions. All four species grew taller, produced more biomass, and increased total root length in wetter treatments. Each species reduced its leaf turgor loss point (TLP) in drier conditions, but only two species (one xeric, one mesic) maintained leaf water potential above TLP. We identified a suite of traits that clearly distinguished species from one another, but, surprisingly, these traits were relatively unresponsive to reduced soil moisture. Specifically, more xeric species produced thinner roots with higher specific root length and had a lower root mass fraction. This suggest that root traits are critical for distinguishing species from one another but might not respond strongly to changing water availability, though this warrants further investigation in the field. Overall, we found that NPP of these dominant grass species responded similarly to varying levels of soil moisture despite differences in species morphology, physiology, and habitat of origin.

Climate disequilibrium dominates uncertainty in long-term projections of primary productivity.

Rapid climate change may exceed ecosystems' capacities to respond through processes including phenotypic plasticity, compositional turnover and evolutionary adaption. However, consequences of the resulting climate disequilibria for ecosystem functioning are rarely considered in projections of climate change impacts. Combining statistical models fit to historical climate data and remotely-sensed estimates of herbaceous net primary productivity with an ensemble of climate models, we demonstrate that assumptions concerning the magnitude of climate disequilibrium are a dominant source of uncertainty: models assuming maximum disequilibrium project widespread decreases in productivity in the western US by 2100, while models assuming minimal disequilibrium project productivity increases. Uncertainty related to climate disequilibrium is larger than uncertainties from variation among climate models or emissions pathways. A better understanding of processes that regulate climate disequilibria is essential for improving long-term projections of ecological responses and informing management to maintain ecosystem functioning at historical baselines.

Biotic vs abiotic controls on temporal sensitivity of primary production to precipitation across North American drylands.

Dryland net primary productivity (NPP) is sensitive to temporal variation in precipitation (PPT), but the magnitude of this 'temporal sensitivity' varies spatially. Hypotheses for spatial variation in temporal sensitivity have often emphasized abiotic factors, such as moisture limitation, while overlooking biotic factors, such as vegetation structure. We tested these hypotheses using spatiotemporal models fit to remote-sensing data sets to assess how vegetation structure and climate influence temporal sensitivity across five dryland ecoregions of the western USA. Temporal sensitivity was higher in locations and ecoregions dominated by herbaceous vegetation. By contrast, much less spatial variation in temporal sensitivity was explained by mean annual PPT. In fact, ecoregion-specific models showed inconsistent associations of sensitivity and PPT; whereas sensitivity decreased with increasing mean annual PPT in most ecoregions, it increased with mean annual PPT in the most arid ecoregion, the hot deserts. The strong, positive influence of herbaceous vegetation on temporal sensitivity indicates that herbaceous-dominated drylands will be particularly sensitive to future increases in precipitation variability and that dramatic changes in cover type caused by invasions or shrub encroachment will lead to changes in dryland NPP dynamics, perhaps independent of changes in precipitation.

Precipitation-productivity relationships and the duration of precipitation anomalies: An underappreciated dimension of climate change.

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.

Plants with lengthened phenophases increase their dominance under warming in an alpine plant community.

Predicting how shifts in plant phenology affect species dominance remains challenging, because plant phenology and species dominance have been largely investigated independently. Moreover, most phenological research has primarily focused on phenological firsts (leaf-out and first flower dates), leading to a lack of representation of phenological lasts (leaf senescence and last flower) and full phenological periods (growing season length and flower duration). Here, we simultaneously investigated the effects of experimental warming on different phenological events of various species and species dominance in an alpine meadow on the Tibetan Plateau. Warming significantly advanced phenological firsts for most species but had variable effects on phenological lasts. As a result, warming tended to extend species' full phenological periods, although this trend was not significant for all species. Experimental warming reduced community evenness and differentially impacted species dominance. Shifts in full phenological periods, rather than a single shift in phenological firsts or phenological lasts, were associated with changes in species dominance. Species with lengthened full phenological periods under warming increased their dominance. Our results advance the understanding of how altered species-specific phenophases relate to changes in community structure in response to climate change.

Precipitation amount and event size interact to reduce ecosystem functioning during dry years in a mesic grassland.

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.

Carbon exchange responses of a mesic grassland to an extreme gradient of precipitation.

Growing evidence indicates that ecosystem processes may be differentially sensitive to dry versus wet years, and that current understanding of how precipitation affects ecosystem processes may not be predictive of responses to extremes. In an experiment within a mesic grassland, we addressed this uncertainty by assessing responses of two key carbon exchange processes-aboveground net primary production (ANPP) and soil respiration (Rs)-to an extensive gradient of growing season precipitation. This gradient comprised 11 levels that specifically included extreme values in precipitation; defined as the 1st, 5th, 95th, and 99th percentiles of the 112-year climate record. Across treatments, our experimental precipitation gradient linearly increased soil moisture availability in the rooting zone (upper 20 cm). Relative to ANPP under nominal precipitation amounts (defined as between the 15th and 85th percentiles), the magnitude of ANPP responses were greatest to extreme increases in precipitation, with an underlying linear response to both precipitation and soil moisture gradients. By contrast, Rs exhibited marginally greater responses to dry versus wet extremes, with a saturating relationship best explaining responses of Rs to both precipitation and soil moisture. Our findings indicate a linear relationship between ANPP and precipitation after incorporating responses to precipitation extremes in the ANPP-precipitation relationship, yet in contrast saturating responses of Rs. As a result, current linear ANPP-precipitation relationships (up to ~ 1000 mm) within mesic grasslands appear to hold as appropriate benchmarks for ecosystems models, yet such models should incorporate nonlinearities in responses of Rs amid increased frequencies and magnitudes of precipitation extremes.

Semiarid ecosystem sensitivity to precipitation extremes: weak evidence for vegetation constraints.

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 saturating NPP-PPT relationships as increases in both dry and wet PPT extremes occur. We experimentally tested this prediction by imposing a replicated gradient of growing season PPT (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: aboveground NPP (ANPP) and soil respiration (Rs ). ANPP and Rs both exhibited greater relative responses to wet vs. dry GSP extremes, with a linear relationship consistently best explaining the response of both processes to GSP. However, this responsiveness to GSP peaked at moderate levels of extremity for both processes, and declined at the most extreme GSP levels, suggesting that greater sensitivity of ANPP and Rs to wet vs. dry conditions may diminish under increased magnitudes of GSP extremes. Underlying these responses was rapid plant compositional change driven by increased forb production and cover as GSP transitioned to extreme wet conditions. This compositional shift increased the magnitude of ANPP responses to wet GSP extremes, as well as the slope and variability explained in the ANPP-GSP relationship. Our findings suggest that rapid plant compositional change may act as a mediator of semiarid ecosystem responses to predicted changes in GSP extremes.

A reality check for climate change experiments: Do they reflect the real world?

Experiments are widely used in ecology, particularly for assessing global change impacts on ecosystem function. However, results from experiments often are inconsistent with observations made under natural conditions, suggesting the need for rigorous comparisons of experimental and observational studies. We conducted such a "reality check" for a grassland ecosystem by compiling results from nine independently conducted climate change experiments. Each experiment manipulated growing season precipitation (GSP) and measured responses in aboveground net primary production (ANPP). We compared results from experiments with long-term (33-yr) annual precipitation and ANPP records to ask if collectively (n = 44 experiment-years) experiments yielded estimates of ANPP, rain-use efficiency (RUE, grams per square meter ANPP per mm precipitation), and the relationship between GSP and ANPP comparable to observations. We found that mean ANPP and RUE from experiments did not deviate from observations. Experiments and observational data also yielded similar functional relationships between ANPP and GSP, but only within the range of historically observed GSP. Fewer experiments imposed extreme levels of GSP (outside the observed 33-yr record), but when these were included, they altered the GSP-ANPP relationship. This result underscores the need for more experiments imposing extreme precipitation levels to resolve how forecast changes in climate regimes will affect ecosystem function in the future.

Ecoevolutionary Dynamics of Carbon Cycling in the Anthropocene.

Climate change is altering natural selection globally, which could shift the evolutionary trajectories of traits central to the carbon (C) cycle. Here, we examine the components necessary for the evolution of C cycling traits to substantially drive changes in global C cycling and integrate these components into a framework of ecoevolutionary dynamics. Recent evidence points to the evolution of C cycling traits during the Anthropocene and the potential to significantly affect atmospheric CO2. We identify directions for further collaboration between evolutionary, ecosystem, and climate scientists to study these ecoevolutionary feedback dynamics and determine whether this evolution will ultimately accelerate or decelerate the current trend in rising atmospheric CO2.

Integrating plant ecological responses to climate extremes from individual to ecosystem levels.

Climate extremes will elicit responses from the individual to the ecosystem level. However, only recently have ecologists begun to synthetically assess responses to climate extremes across multiple levels of ecological organization. We review the literature to examine how plant responses vary and interact across levels of organization, focusing on how individual, population and community responses may inform ecosystem-level responses in herbaceous and forest plant communities. We report a high degree of variability at the individual level, and a consequential inconsistency in the translation of individual or population responses to directional changes in community- or ecosystem-level processes. The scaling of individual or population responses to community or ecosystem responses is often predicated upon the functional identity of the species in the community, in particular, the dominant species. Furthermore, the reported stability in plant community composition and functioning with respect to extremes is often driven by processes that operate at the community level, such as species niche partitioning and compensatory responses during or after the event. Future research efforts would benefit from assessing ecological responses across multiple levels of organization, as this will provide both a holistic and mechanistic understanding of ecosystem responses to increasing climatic variability.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'.

Linking Changes to Intraspecific Trait Diversity to Community Functional Diversity and Biomass in Response to Snow and Nitrogen Addition Within an Inner Mongolian Grassland.

In recent years, both the intraspecific and interspecific functional diversity (FD) of plant communities have been studied with new approaches to improve an understanding about the mechanisms underlying plant species coexistence. Yet, little is known about how global change drivers will impact intraspecific FD and trait overlap among species, and in particular how this may scale to impacts on community level FD and ecosystem functioning. To address this uncertainty, we assessed the direct and indirect responses of specific leaf area (SLA) among both dominant annual and subordinate perennial species to the independent and interactive effects of nitrogen and snow addition within the Inner Mongnolian steppe. More specifically, we investigated the consequences for these responses on plant community FD, trait overlap and biomass. Nitrogen addition increased the biomass of the dominant annual species and as a result increased total community biomass. This occurred despite concurrent decreases in the biomass of subordinate perennial species. Nitrogen addition also increased intraspecific FD and trait overlap of both annual species and perennial species, and consequently increased the degree of trait overlap in SLA at the community level. However, snow addition did not significantly impact intraspecific FD and trait overlap of SLA for perennial species, but increased intraspecific FD and trait overlap of annual species, of which scaled to changes in community level FD. We found that the responses of the dominant annual species to nitrogen and snow additions were generally more sensitive than the subordinate perennial species within the inner Mongolian grassland communities of our study. As a consequence of this sensitivity, the responses of the dominant species largely drove impacts to community FD, trait overlap and community biomass. In total, our study demonstrates that the responses of dominant species in a community to environmental change may drive the initial trajectories of change to community FD and functioning.

Underappreciated problems of low replication in ecological field studies.

The cost and difficulty of manipulative field studies makes low statistical power a pervasive issue throughout most ecological subdisciplines. Ecologists are already aware that small sample sizes increase the probability of committing Type II errors. In this article, we address a relatively unknown problem with low power: underpowered studies must overestimate small effect sizes in order to achieve statistical significance. First, we describe how low replication coupled with weak effect sizes leads to Type M errors, or exaggerated effect sizes. We then conduct a meta-analysis to determine the average statistical power and Type M error rate for manipulative field experiments that address important questions related to global change; global warming, biodiversity loss, and drought. Finally, we provide recommendations for avoiding Type M errors and constraining estimates of effect size from underpowered studies.